Uplink Access Protocol In IEEE 802.11AC

Uplink Access Protocol In IEEE 802.11AC

ABSTRACT

IEEE 802.11ac amendment enhances WLANthroughput by exploiting spatial diversity of antennas in MUMIMO downlink transmission. Still, network resources remainunder-utilized in uplink transmission due to single user communication. This project proposes an Access Point-controlledMAC protocol (A-MAC) that enables simultaneous transmissions from multiple STAs in uplink. The protocol uses EDCAchannel access technique to initiate multi-user transmission and OFDMA method to transmit multiple RTSs simultaneously. Italso introduces explicit channel sounding technique by usingdedicated OFDM subcarrier blocks for each user. Performancemeasurement shows that network throughput of the A-MAC is150% higher than that of a single uplink transmission, thanksto the availability of concurrent multiple RTS transmissions inthe uplink.

 INTRODUCTION

IEEE 802.11 protocol is continuously evolving to keep pacewith the growing need for high speed broadband multimediacommunication. IEEE 802.11ac is a recent amendment thatsupports point-to-multipoint communication in the downlink(DL) using pioneering multi-input multi-output (MIMO) technique. DL-MIMOincreases the network throughput by allowing transmission to maximum four STAs simultaneouslyusing spatial multiplexing. The protocol still uses one-to-onecommunication in the uplink direction which keeps the abundant resources in AP under-utilized. In fact, the throughputof WLANs scales linearly with the multi packet reception(MPR) capability of the channel.

The technical challengesof multiple concurrent uplink transmissions require the APreceiver to perform per-user channel estimation, and carrierfrequency offset estimation due to RF mismatches betweenSTAs and AP. Without precise channel state information(CSI), space diversity through beamforming technique cannotbe utilized in the uplink due to overlapping of multipletransmitting signals at AP.

In IEEE802.11ac protocol, channel state information is obtained bythe training bits in the preamble. However, to determinechannel state effectively, preamble transmission must be ina clear channel state which means that, during multiple uplinktransmission, interference-free preamble detection cannot beguaranteed. Therefore, an explicit channel sounding techniqueis required for uplink MU-MIMO transmission.

EXISTING SYSTEM:

 Zhou and Z. Niu, “An Uplink Medium Access Protocol withSDMA Support for Multiple-Antenna WLANs,” in Proc. of IEEEWireless Communications and Networking Conference. pp. 1809–1814,Mar. 2008.

The MAC protocol proposed requires a majorchange in the IEEE 802.11 protocol. The inclusion of multipleRTS/CTS during random access period increases the overheadburden to the protocol and, consequently, reduces networkthroughput and efficiency.

Tandai, H. Mori, K. Toshimitsu, and T. Kobayashi, “An efficientuplink multiuser MIMO protocol in IEEE 802.11 WLANs,” in Proc.of IEEE 20th International Symposium on Personal, Indoor and MobileRadio Communications. pp. 1153–1157, Sept. 2009

An uplink MMSE detection based MU-MIMO protocol isproposed for the IEEE 802.11 WLAN. In this protocolSTAs use OFDMA technique to transmit access request to APand TDMA technique to transmit pilot signals.

 PROPOSED SYSTEM:

An EDCAbased uplink transmission technique is proposed for non-HE devices thatallows multi-user transmission to improve spectral efficiencyin a coexistent WLAN network. An Access Pointcontrolled contentionbased MAC protocol (A-MAC) andexplicit channel sounding technique is proposed that allow multi-user concurrent uplink transmission within IEEE 802.11ac frameworkkeeping compatibility with the downlink MU-MIMO technique. The proposed protocol is a step towards implementingthe desired throughput enhancement using concurrent multipleuplink transmissions and MIMO-OFDMA techniques. Themajor contributions are:

  • Introduce explicit channel sounding technique byusing dedicated subcarrier blocks.
    Develop an analytical model using queuing model andMarkov chain model to evaluate the performance of theproposed A-MAC.
  • Evaluate the performance metrics of proposed AMAC protocol for bothuniformly and non-uniformlyvarying packet arrival rates for different priority categories.
  • Develop the stable operating criterion for the networkfor varying traffic conditions.
  • The proposed protocol provides a green solution byreducing the backoff time and thereby increasing theefficiency of the network.

ADVANTAGES

  • Shortens the backoff timeby up to 50% for all traffic categories.
  • Enhances battery life of thenodes.
  • The smaller backoff windowof high priority traffic category enhances network throughput,higher intensity of high priority traffic drives the network fasterto saturation.
  • Better network stability and fairnessamong different traffic categories can be achieved when thedominant traffic has low priority.

BLOCK DIAGRAM

DESCRIPTION

The frame exchange sequence of the proposed protocol medium becomes idle, all STAs start backoff process. When STA1 wins the contention,STA1 sends RTS. Since the network does not have anyhidden terminals and all STAs hear each other, the AP andSTAs have the knowledge about the collision of first roundRTS. If the collision happens, the primary STA initiates nextbackoff phase. On hearing RTS, secondary STAs suppress the backoff counting and update the NAV according to theduration information in RTS. Receiving STAs (including AP)decode RTS signal to find the intended destination address.

Ifthe RTS is intended for AP and AP decides to allow multiuser transmission, AP defers the transmission of G-CTS upto DIFS period. If AP cannot allow multiple transmission simultaneously, it sends CTS after SIFS period as shown in Fig3. If primary STA listens CTS after SIFS period, the primary STA starts data transmission after SIFS period and other STAskeep the backoff countdown suppressed until the medium isidle again. However, if no CTS is transmitted by AP to primary STA after SIFS period, other STAs are allowed to transmitconcurrent RTSs using previously allocated OFDM subcarrierblocks. It is fair to assume that AP is connected to the infrastructure and has no capability constrain in monitoring each subcarrier block to retrieve all secondary RTSs. Depending on the number of STAs, it is possible that AP receives larger number of RTSs than the number of antennas Mant in AP.

SYSTEM  IMPLEMENTATION:

Tool                               :         MATLAB 8.1

Platform                         :         Windows/linux

Scripting Language        :         C / Matlab coding

 

REFERENCE:

Zulfiker Ali and Jelena,” Uplink Access Protocol in IEEE 802.11ac” IEEE Transactions on Wireless Communications, 2018

Ultra-Dense Hetnets Meet Big Data: GreenFrameworks, Techniques, and Approaches

Ultra-Dense Hetnets Meet Big Data: GreenFrameworks, Techniques, and Approaches

ABSTRACT

Ultra-dense heterogeneous networks (Ud-HetNets) have been put forward to improve the network capacity for next-generation wireless networks. However, counter to the 5G vision, ultra-dense deployment of networks would significantly increase energy consumption and thus decrease network energy efficiency, suffering from the conventional worst case network design philosophy. This problem becomes particularly severe when Ud-HetNets meet big data because of the traditional reactive request-transmit service mode. In view of these, this project first develops a big-data-aware artifcial-intelligence-based framework for energy-efficient operations of Ud-HetNets. Based on the framework, we then identify four promising techniques, namely big data analysis, adaptive base station operation, proactive caching, and interference-aware resource allocation, to reduce energy cost on both large and small scales. Further, the development of a load-aware stochastic optimization approach is done to show the potential of our proposed framework and techniques in energy conservation. In a nutshell, green Ud-HetNets of big data with the abilities of learning and inferring by improving the flexibility of control from worst case to adaptive design and shifting the manner of services from reactive to proactive modes is constructed.

INTRODUCTION

With the flourish of the Internet of Things (IoT),the amount of mobile devices increases explosively, and correspondingly, the massive connectionsbetween humans, humans and machines, andmachines skyrocket continuously. These in turnboost the exponential growth of wireless trafficvolumes, resulting in a 1000-fold data challenge to wireless networks. On the other hand, available spectrum resources that can be allocated towireless networks are becoming scarcer and scarcer, so it is impractical to dramatically improve thenetwork capacity by continuously obtaining additional spectrum. As a result, more advanced network organization and wireless technologies areeagerly needed to improve the network capacity.

EXISTING SYSTEM:

Niu et al., “Cell Zooming for Cost-Efficient Green Cellular Networks,”IEEE Commun. Mag., vol. 48, no. 11, Nov.2010, pp. 74–79.

Proposedthe technique of cell zooming, where the cell sizeis tuned with traffic load fluctuations for energycontrol.

 Kim, S. Choi, and B. G. Lee, “A Joint Algorithm for BaseStation Operation and User Association in HeterogeneousNetworks,” IEEE Commun. Lett., vol. 17, no. 8, Aug. 2013,pp. 1552–55

Jointly optimized BS operation and userassociation to reveal energy-delay and energy-revenue trade-offs, respectively.

 PROPOSED SYSTEM:

Ud-HetNets have been proposed as an important network organization architecture to improvenetwork capacity. With the exponential growthof mobile trafc volumes, Ud-HetNets are boundto be networks of big data. Ud-HetNets of bigdata impose great challenges on their practicaldeployment due to the incurred huge energy consumption. In this Project, first a big-data-aware AI-based network framework is developed forenergy-efficient operations of Ud-HetNets. Then identified four promising techniques,namely big data analysis, adaptive BS operation, proactive caching, and interference-awareresource allocation. The framework and theserelated techniques enable the network with theabilities of learning and inferring by analyzingthe collected big data, and then save energyfrom both large scales (BS operation) and small scales (proactive caching and interference-aware resource allocation). Further establisheda load-aware stochastic optimization model toshow the potential of our proposed frameworkand techniques in reducing energy consumption.

ADVANTAGES

  • Improves the networkcapacity.
  • Energy-efficient operations
  • Reduce energy cost on both large and smallscales.

BLOCK DIAGRAM

DESCRIPTION

Centralized BBU Pool: In Ud-HetNets,macro BSs (MBSs) are kept for improvingmobility performance and reducing ping-pongeffects, while parts of small cell BSs (SBSs) aresplit into baseband units (BBUs) and remoteradio heads (RRHs), with their interconnectionvia high-bandwidth low-latency optical transportnetworks. Then BBUs are integrated into centralized BBU pools, responsible for intelligentresource allocation and signal processing withthe help of cloud computing and virtualizationtechniques and RRHs for information radiation. The MBSs and BBU pool are connected tothe big-data-aware intelligent platform throughgateways, which are then associated with thecore network. Thus, the centralized BBU poolswith strong computing and coordinating abilities facilitate the sharing of information amongcells and RANs, which paves the path for intelligent resource optimization.

Social Networks: With the ever increasingpopularity of social platforms such as Facebookand Wechat, social networks have become animportant part of Ud-HetNets of big data. Unlikecommunication entities (e.g., MBSs and BBUs),social networks, almost irrelevant to physical
entities, are used to describe the relationshipsbetween/among users in networks, regardless ofwhether they are close to each other or locatedin different areas.

Big-Data-Aware Intelligent Platform: The big-data-aware intelligentplatform is implemented between the gatewayand the core network, consisting of a big datacenter, a database, and a learning system. First, raw data generated in Ud-HetNets is collected and pre-processed by the big data center. Then, throughAI-based data analysis, user behaviors and network patterns are extracted from clear data andrelated results as well as useful history data arestored in the database, which are later used totrain the learning system.

SYSTEM  IMPLEMENTATION

Tool                               :         MATLAB 8.1

Platform                         :         Windows/linux

Scripting Language        :         C / Matlab coding

REFERENCE:

Yuzhou Li, Yu Zhang, Kai Luo, Tao Jiang, Zan Li, and Wei Peng , ”Ultra-Dense HetNets Meet Big Data: GreenFrameworks, Techniques, and Approaches”IEEE Communications Magazine • June 2018

 

Time-to-Space Division Multiplexing for Tb/s Mobile Cells

Time-to-Space Division Multiplexing for Tb/s Mobile Cells

ABSTRACT

Space division multiplexing increases the capacity of mobile cells by reusing the frequencies in various directions. Yet, today’s concepts scale badly to millimeter wave and therefore cannot provide Tb/s capacity. In this paper, we introduce time-to-space division multiplexing as a novel scheme to steer multiple beams simultaneously to different users. The main benefit of the proposed method relies in the fact that simple hardware can be used to generate the beams. In other word, it provides the advantages of space division multiplexing without relying on the complex array feeders that are usually required.

INTRODUCTION

Space division multiplexing (SDM) and millimeter wave communication – if applied together – could offer Tb/s of wireless capacity. Yet, an affordable solution to merge the advantages of both technologies is very challenging to be found . SDM requires either massive hardware in the form of multiple phased-array antennas or large digital signal processing (DSP) capacities. Yet, DSP is particularly expensive at highest speed such as those needed to encode millimeter wave signals. If Tb/s wireless links are to become practical new solutions that rely on low complexity and low-cost hardware will be needed .

Among the most promising implementations of next generation radio access networks (NG RAN), two trends can be distinguished: First, concepts relying on current 4G-LTE microwave frequencies (2.4, 5 GHz) with approaches such as massive multiple input, multiple output (MIMO) or smarter networks . Second, concepts based on millimeter wave (mm-Wave) technologies . In the case of massive MIMO , e.g. E. Larsson et al. take advantage of low-cost, reliable, and mass producible components to generate multiple beams, but suffer from the limited bandwidth available at microwave frequencies.

EXISTING SYSTEM:

Zhouyue and F. Khan, “An introduction to millimeter-wave mobile broadband systems,” IEEE Commun. Mag., vol. 49, no. 6, pp. 101-107, 2011.

Smarter networks with mm-Wave technologies could potentially combine the benefits of both approaches to provide both a larger bandwidth and spatial diversity at the same time

Alkhateeb, J. Mo, N. Gonzalez-Prelcic, and R. W. Heath, “MIMO precoding and combining solutions for millimeter-wave systems,” IEEE Commun. Mag., vol. 52, no. 12, pp. 122-131, 2014..

Merging both approaches has shown to be challenging with current designs due to the large number of mm-Wave components in the base band units (BBU), the remote radio head (RRH), and the user equipment (UEs)

 PROPOSED SYSTEM:

In this paper, a next generation (NG) RAN scheme relying on already published ultra-fast mm-Wave beam steering demonstrations is presented . The scheme, which is termed time-to-space division multiplexing (TSDM), increases the capacity of a mobile cell while simultaneously drastically reducing the hardware requirements on the UEs. In other words, TSDM enables multiple beam steering capabilities comparable to concepts such as known from massive MIMO or multiple beam array feeders , but with a fraction of the hardware requirements at mm-Waves. Leveraging the advantages of TSDM, we propose the design of a mobile cell with an aggregated capacity above 1 Tb/s, meeting the frequency band specifications of the IEEE 802.11ad standard.

 ADVANTAGES

  • Minimal Probe Is Estimated That Is Adapted To The Network
  • The Minimal Probe Is Used To Obtain A Service Curve Estimate With A Defined Accuracy.
  • While Delays In The Range Of Seconds Have Been Measured For Edge And Hspa, It Has Been Found That Lte Achieves An Improvement by an order of magnitude.

BLOCK DIAGRAM

Another way of increasing the cell capacity by orders of magnitude is to use SDM. SDM is based on reusing the same frequency band in various directions by forming spatially separated, non-interfering radio beams . This corresponds to the creation of virtual cell sectors with adaptive coverage. If a user receives the signal from only one beam at a time, it results in two advantages: first, the cell capacity is increased by the number of spatially separated beams. Second, the full UE capacity can be used since neither time, code, nor frequency multiplexing is required. Hence, there is a need of phased array antenna (PAA) concepts capable of simultaneous and independent steering of multiple antenna beams. In order to compare the various implementations of PAA, three main categories of feeders can be defined, see Fig. 1.

SYSTEM  IMPLEMENTATION

Tool                               :         MATLAB 8.1

Platform                         :         Windows/linux

Scripting Language        :         C / Matlab coding

REFERENCE:

Romain Bonjour , Member, IEEE, Samuel Welschen, and Juerg Leuthold, Fellow, IEEE, “Time-to-Space Division Multiplexingfor Tb/s Mobile Cells”, IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 17, NO. 7, JULY 2018.

 

Throughput Maximization for Multi-HopDecode-And-Forward Relay Network withWireless Energy Harvesting

Throughput Maximization for Multi-HopDecode-And-Forward Relay Network withWireless Energy Harvesting

ABSTRACT

Consider the multi-hop wireless networks with decode-and-forward relays.Intermediate relays have no fixed power supplies and thus need to replenish energy via wireless energyharvesting from the source signal. The technique of simultaneous wireless information and power transfer(SWIPT) is utilized between every two adjacent nodes to transport both information and energy. Threegeneral protocols of SWIPT are considered: power-splitting (PS), time-switching (TS), and hybrid whichis a combination of PS and TS protocols. For each protocol,  Formulate optimization problems to decideoptimal PS and TS ratios so as to maximize end-to-end throughput under two schemes. Scheme 1 allowsdifferent PS and TS ratios at each relay, and Scheme 2 uses uniform PS and TS ratios for all the relays. Theproposed optimization problems are shown to be non-convex. With a series of transformations, the proposed non-convex optimization problems to be convex ones are turned.

INTRODUCTION

Multi-hop wireless relaying network is a promising solutionfor extending coverage and enhancing system performancefor wireless communication, and is especially useful forwireless sensor network (WSN), Internet of Things (IoT),and small-scale indoor networks. The multi-hop wireless relaying network in a WSN, IoT, or small-scale indoornetwork, requires stable energy supply for relay nodes sincereplacing the build-in battery of relay nodes involves great expenses. One candidate solution is the wireless energyharvesting (EH) technique.

Generally there are three categories of wireless EH: 1) Near field transfer via magnetic induction, resonant coupling, or capacitive coupling,which will be effective within one meter and can transfermultiple watts of power; 2) Far field transfer via directivepower beaming, which can transfer several milliwatts ofpower at a distance of several meters; 3) Far field transfer via scavenging several microwatts of power from ambient RFsignal sent by cellular base station and TV tower, generallyhundreds or thousands of meters away. Among these threetechniques, far field transfer via directive power beamingis preferable since it can offer enough power at a relativelong distance for a multiple-hop relaying network. In thispaper, we will adopt the far field transfer via directive powerbeaming as the wireless EH solution for multi-hop wirelessnetwork. For the ease of presentation, when wireless EH ismentioned in the following, we mean far field transfer via
directive power beaming is utilized.

EXISTING SYSTEM:

 A. Nasir, X. Zhou, S. Durrani, and R. A. Kennedy, ‘‘Relaying protocolsfor wireless energy harvesting and information processing,’’ IEEE Trans.Wireless Commun., vol. 12, no. 7, pp. 3622–3636, Jul. 2013.

Analytical expression ofergodic capacity and outage capacity are deduced under PSprotocol and TS protocol for a DF relay network powered bythe signal from source node.

Ding, S. M. Perlaza, I. Esnaola, and H. V. Poor, ‘‘Power allocation strategies in energy harvesting wireless cooperative networks,’’ IEEE Trans.Wireless Commun., vol. 13, no. 2, pp. 846–860, Feb. 2014

Multiple source-destination pairs are aided via one DFrelay node, which is wireless powered by multiple sourcenodes. Outage performance is analyzed under various transmission power allocation strategies for forwarding information from the relay node to the destination node.

 PROPOSED SYSTEM:

The Proposed method investigated the end-to-end throughput maximization problem in a wireless EH multi-hop relay network under three SWIPT protocols. Separate and uniform PS ratio and/or TS ratio in each hop are optimized in order to maximize the end-to-end throughput. The original forms of proposed optimal resource allocation problems in this method are non-convex, which makes it hard to find the global optimal solutions. With a series of technical transformations, the formulated non-convex optimization problems are converted to be convex ones for the first time. Thus global optimal solutions are achievable. Apart from these theoretical contributions, this method also analyzes the performance under the distance dependent path loss model and the ITU indoor propagation model which highlights a tradeoff between number of intermediate relays and throughput for some practical network parameters.

ADVANTAGES

  • High transmit power region,
  • PS protocol is a good candidate to achieve the trade-off between performance and implementation complexity.
  • End-to-end throughput is maximized by optimization of the PS ratio and TS ratio under two schemes.

BLOCK DIAGRAM

DESCRIPTION

The source node sends information to its destination via M intermediate DF relay.Thus, there are MC1 hops between source and destination. When RF signal is forwarded, SWIPT is utilized only between two neighboring nodes at a time, by assuming that non-neighboring channels are sufficiently weak to be ignored due to obstacles and/or deep fading. Denote the channel coefficient between intermediate nodes as hm, which is comprised of two components: i) the distance dependent path loss such that the received power decays with the distance1; and ii) multipath fading. All the channels are assumed to be independent. During the packet transmission, the channel coefficient does not change. Every relay node has a single antenna and works in halfduplex mode. Therefore, only after receiving a whole packet, the rely node can send the packet to the next node.

The communication occurs in time-slot basis so that the slot length is the time required to transmit one packet.The hybrid protocol is assumed for the wireless EH relay network because this can derive PS and TS protocols. Source Node is the only node in the network with fixed energy supply, while the intermediate nodes have to harvest energy from RF signals. Denote the transmission block period between two neighboring nodes as T which is for both EH and information receiving. Thus each intermediate relay is active for time 2T.

SYSTEM  IMPLEMENTATION

Tool                               :         MATLAB 8.1

Platform                         :         Windows/linux

Scripting Language        :         C / Matlab coding

REFERENCE:

RONGFEI FAN  and SAMAN ATAPATTU, “Throughput Maximization for Multi-HopDecode-and-Forward Relay Network With Wireless Energy Harvesting” IEEE ACCESS April 30, 2018.

 

Super-Resolution Channel Estimation for MmWave Massive MIMO with Hybrid Precoding

Super-Resolution Channel Estimation for MmWave Massive MIMO with Hybrid Precoding

ABSTRACT

Channel estimation is challenging for millimeterwave (mmWave) massive MIMO with hybrid precoding, since the number of radio frequency (RF) chains is much smaller than that of antennas. Conventional compressive sensing based channel estimation schemes suffer from severe resolution loss due to the channel angle quantization. To improve the channel estimation accuracy, we propose an iterative reweight (IR)-based superresolution channel estimation scheme in this paper.

INTRODUCTION

Millimeter-wave (mmWave) massive MIMO has been recognized as a promising technology for future 5G wireless communications. To reduce the hardware cost and power consumption, hybrid precoding has been proposed for practical mmWave massive MIMO systems, where hundreds of antennas are driven by a much smaller number of radio frequency (RF) chains . The analog and digital codesign in hybrid precoding requires accurate channel state  information. However, the digital baseband cannot directly access all antennas due to the small number of RF chains, so it is difficult to accurately estimate the high-dimensional MIMO channel. Several novel channel estimation schemes have been recently proposed for mmWave massive MIMO with hybrid precoding.

EXISTING SYSTEM:

Hur, T. Kim, D. J. Love, J. V. Krogmeier, T. A. Thomas, and A. Ghosh, “Millimeter wave beamforming for wireless backhaul and access in small cell networks,” IEEE Trans. Commun., vol. 61, no. 10, pp. 4391- 4403, Oct. 2013..

The adaptive codebook-based channel sounding scheme, where the transmitter and receiver search for the best beam pair by adjusting the predefined precoding and combining codebooks.

 Zhu, J. Choi, and R. W. Heath, “Auxiliary beam pair enabled AoD and AoA estimation in closed-loop large-scale millimeter-wave MIMO systems,” IEEE Trans. Wireless Commun., vol. 16, no. 7, pp. 4770-4785, May 2017.

The channel estimation resolution is limited by the codebook size.was able to achieve better angle estimation by performing an amplitude comparison with respect to the auxiliary beam pair.

 PROPOSED SYSTEM:

Optimizing an objective function through the gradient descent method, the proposed scheme can iteratively move the estimated angle of arrivals/departures (AoAs/AoDs) towards the optimal solutions, and finally realize the super-resolution channel estimation. In the optimization, a weight parameter is used to control the tradeoff between the sparsity and the data fitting error. In addition, a singular value decomposition (SVD)-based preconditioning is developed to reduce the computational complexity of the proposed scheme. Simulation results verify the better performance of the proposed scheme than conventional solutions..

ADVANTAGES

  • Iteratively moves them to the neighboring offgrid actual positions via gradient descent method
  • SVD-based preconditioning to reduce the computational complexity.
  • The proposed super-resolution channel estimation scheme can advance the state-of-art by estimating the off-grid AoAs/AoDs with much increased accuracy.
  • Practical way to realize higher spectral efficiency

BLOCK DIAGRAM

We consider a hybrid-precoding mmWave massive MIMO with arbitrary array geometry. Let NT, NR, NRF T , and NRF R be the number of transmit antennas, receive antennas, transmitter RF chains, and receiver RF chains, respectively. For practical mmWave massive MIMO with hybrid precoding, the number of RF chains is much smaller than that of antennas, i.e…

Proposed Optimization Formulation

The main difficulty in solving (8) lies in the fact that the l0- norm is not computationally efficient for finding the optimal solution. By replacing the l0-norm with a log-sum function , we have

IR-Based Super-Resolution Channel Estimation

In the previous subsection, we have already simplified the constrained optimization problem (8) to an unconstrained angle optimization problem (14). To solve this reformulated problem, now we propose an IR-based super-resolution channel estimation scheme as described.

SYSTEM  IMPLEMENTATION:

Tool                               :         MATLAB 8.1

Platform                         :         Windows/linux

Scripting Language        :         C / Matlab coding

REFERENCE:

Chen Hu, Linglong Dai, Senior Member, IEEE, Talha Mir, Zhen Gao, Member, IEEE,and Jun Fang, Senior Member, IEEE, “Super-Resolution Channel Estimation for MmWaveMassive MIMO with Hybrid Precoding”, IEEETransactions on Vehicular Technology, 2018.

Spatially Random Relay Selection for Full/Half-Duplex Cooperative NOMA Networks

Spatially Random Relay Selection for Full/Half-Duplex Cooperative NOMA Networks

ABSTRACT

This project investigates the impact of relay selection (RS) on the performance of cooperative non-orthogonal multiple access (NOMA), where relays are capable of working in either full-duplex (FD) or half-duplex (HD) mode. A number of relays (i.e., K relays) are uniformly distributed within the disc. A pair of RS schemes are considered insightfully: 1) Single-stage RS (SRS) scheme; and 2) Two-stage RS (TRS) scheme. In order to characterize the performance of these two RS schemes, new closed-form expressions for both exact and asymptotic outage probabilities are derived. Based on analytical results, the diversity orders achieved by the pair of RS schemes for FD/HD cooperative NOMA are obtained. Our analytical results reveal that: i) The FD-based RS schemes obtain a zero diversity order, which is due to the influence of loop interference (LI) at the relay; and ii) The HD-based RS schemes are capable of achieving a diversity order of K, which is equal to the number of relays. Finally, simulation results demonstrate that: 1) The FD-based RS schemes have better outage performance than HD-based RS schemes in the low signal-to-noise radio (SNR) region; 2) As the number of relays increases, the pair of RS schemes considered are capable of achieving the lower outage probability; and 3) The outage behaviors of FD/HD-based NOMA SRS/TRS schemes are superior to that of random RS (RRS) and orthogonal multiple access (OMA) based RS schemes.

INTRODUCTION

With the rapid advancement in the wireless communicationtechnology, the fifth generation (5G) mobile communicationnetworks have attracted a great deal of attention. Inparticular, three major families of new radio (NR) usage scenarios, i.e., massive machine type communications (mMTC),enhanced mobile broadband (eMBB) and ultra-reliable and low-latency communications (URLLC) are proposed to satisfy the different requirements for 5G networks. To improvesystem throughput and achieve enhanced spectrum efficiencyof 5G networks, non-orthogonal multiple access (NOMA) hasbeen considered to be a promising candidate technique andidentified for 3GPP Long Term Evolution (LTE). The coreidea of NOMA is able to multiplex additional users in thesame physical resource. More specifically, the superpositioncoding scheme is employed at the transmitting end, where thelinear superposition of signals of multiple users is formed tobe the transmit signal. The successive interference cancellation(SIC) procedure is carried out by the receiving end who has thebetter channel conditions. Furthermore, downlink multiusersuperposition transmission scheme (MUST) which is thespecial case of NOMA has found application in wirelessstandard.

EXISTING SYSTEM:

 Xu, Y. Yuan, Z. Ding, X. Dai, and R. Schober, “On the outageperformance of non-orthogonal multiple access with 1-bit feedback,”IEEE Trans. Wireless Commun., vol. 15, no. 10, pp. 6716–6730, Oct.2016.

Researched theoutage behavior of downlink NOMA for the case where eachNOMA user only feedbackone bit of its channel state information (CSI) to a base station (BS). It was shown that NOMAis capable of providing higher fairness for multiple userscompared to conventional opportunistic one-bit feedback.

Ding, P. Fan, G. K. Karagiannidis, R. Schober, and H. V.Poor, “NOMA assisted wireless caching: Strategies and performanceanalysis,” 2017.

The NOMA-based wireless cashing strategies were introducedin which two cashing phases, i.e., content pushingand content delivery, are characterized in terms of caching hitprobability.

PROPOSED SYSTEM:

More specifically, In theSRS scheme, the data rate of distant user is ensured to selecta relay as its helper to forward the information. In the TRSscheme, on the condition of ensuring the data rate of distantuser, Serve the nearby user with data rate as large aspossible for selecting a relay. Based on the proposed schemes,the primary contributions can be summarized as follows:

  • Investigate the outage behaviors of two RS schemes(i.e., SRS scheme and TRS scheme) for FD NOMAnetworks. We derive the closed-form and asymptoticexpressions of outage probability for FD-based NOMARS schemes. Due to the influence of residual LI atrelays, a pair of FD-based NOMA RS schemes convergeto an error floor in the high signal-to-noise radio (SNR)region and provide zero diversity order.
  • Also derive the closed-form expressions of outageprobability for two HD-based NOMA RS schemes. To get more insights, the asymptotic outage probabilities ofHD-based NOMA RS schemes are derived. We observethat with the number of relays increasing, the lower outage probability can be achieved for HD-based NOMARS schemes. We confirm that the HD-based NOMA RSschemes are capable of providing the diversity order ofK, which is equal to the number of relays.
  • Show that the outage behaviors of FD-based NOMASRS/TRS schemes are superior to that of HD-basedNOMA SRS/TRS schemes in the low SNR region ratherthan in the high SNR region. Furthermore, we confirmthat the FD/HD-based NOMA TRS/SRS schemes arecapable of providing better outage performance compareto random RS (RRS) and orthogonal multiple access(OMA) based RS schemes. Additionally, we analyze thesystem throughput in delay-limited transmission modebased on the outage probabilities derived.

ADVANTAGES

  • The pair of RS schemes considered are capable of achieving the lower outage probability;
  • The outage behaviors of FD/HD-based NOMA SRS/TRS schemes are superior to that of random RS (RRS) and orthogonal multiple access (OMA) based RS schemes.

BLOCK DIAGRAM

The DF protocol is employed at each relay and onlyone relay is selected to assist BS conveying the information tothe NOMA users in each time slot. To enable FD operation,each relay is equipped with one transmit antenna and onereceive antenna, while the BS and users have a single antenna respectively. All wireless channels2 in the scenario consideredare assumed to be independent non-selective block Rayleighfading and are disturbed by additive white Gaussian noise withmean power N0. Assuming that an imperfect self-interference cancellation scheme is employed at each relay and the corresponding LI is modeled as a Rayleigh fading channel with coefficient. Two NOMA users are classified into the nearby user anddistant user by their quality of service (QoS) not sorted bytheir channel conditions. More particularly, via the assistanceof the best relay selected, the QoS requirements of NOMAusers can be supported effectively for the IoT scenarios (i.e.,small packet business and telemedicine service).  HenceAssume that D1 can be served opportunistically and D2needs to be served quickly for small packet with a lower targetdata rate.

SYSTEM  IMPLEMENTATION

Tool                               :         MATLAB 8.1

Platform                         :         Windows/linux

Scripting Language        :         C / Matlab coding

REFERENCE:

Xinwei Yueand Yuanwei Liu, “Spatially Random Relay Selection for Full/Half-Duplex Cooperative NOMA Networks”,IEEETransactions on Communications, 2018.

 

Slice asan Evolutionary Service: GeneticOptimization For Inter-Slice ResourceManagement In 5G Networks

Slice asan Evolutionary Service: GeneticOptimization For Inter-Slice ResourceManagement In 5G Networks

ABSTRACT

In the context of fifth-generation mobile networks, the concept of ‘‘Slice as a Service’’ promotesmobile network operators to flexibly share infrastructures with mobile service providers and stakeholders.However, it also challenges with an emerging demand for efficient online algorithms to optimize therequest-and-decision-based inter-slice resource management strategy. Based on genetic algorithms, thisproject presents a novel online optimizer that efficiently approaches toward the ideal slicing strategy withmaximized long-term network utility. The proposed method encodes slicing strategies into binary sequencesto cope with the request-and-decision mechanism. It requires no a priori knowledge about the traffic/utilitymodels and therefore supports heterogeneous slices while providing solid effectiveness, good robustnessagainst non-stationary service scenarios, and high scalability.

INTRODUCTION

Network slicing was proposed by the Next Generation MobileNetworks (NGMN) Alliance. Since then, it has becomeone of the hottest topics in the filed of future 5th Generation (5G) mobile communication networks. Generally,the concept of network slicing can be understood as creatingand maintaining multiple independent logical networks on acommon physical infrastructure platform, every slice operates a separate business service with certain Quality ofService (QoS) requirements. Enabled and supported by theemerging technologies of software defined networks (SDN)and network function virtualization (NFV), network slicingexhibits great potentials not onlyin supporting specialized applications with extreme performance requirements, but also in benefiting the mobilenetwork operators (MNOs) with increased revenue. A slicedmobile network manages its infrastructure and virtualresources in independent scalable slices, each slice runs ahomogeneous service with a specific business model. Thus,an MNO can dynamically and flexibly create, terminate andscale its slices to optimize the resource utilization.

EXISTING SYSTEM:

Han, S. Tayade, and H. D. Schotten, ‘‘Modeling profit of sliced5G networks for advanced network resource management and sliceimplementation,’’ in Proc. 22nd IEEE Symp. Comput. Commun. (ISCC),Jul. 2017, pp. 576–581.

Proposed a profit optimization model for sliced mobile networks that applies on thetraditional business mode: the MNOs with network resourcesimplement the slices and provide all network services directlyto their end-users. In this case, a MNO is fully awareof a priori knowledge about the service demands and thecost/revenue models of every slice.

 Bega, M. Gramaglia, A. Banchs, V. Sciancalepore, K. Samdanis, andX. Costa-Perez, ‘‘Optimising 5G infrastructure markets: The businessof network slicing,’’ in Proc. 36th IEEE Int. Conf. Comput. Commun.(INFOCOM), May 2017, pp. 1–9

Elastic slices can be defined to guarantee anaverage QoS level for a lower payment, while inelasticslices provide guaranteed minimal QoS level for a higherpayment.

 PROPOSED SYSTEM:

This project presented a novel online genetic slicingstrategy optimizer to maximize the long-term network utilityin SlaaS. It encodesslicing strategies instead of resource schedules into binarysequences, which enables genetic optimization for inter-sliceresource management based on tenant requests and MNO’s binary decisions. Besides, it requires no a priori knowledgeabout the traffic or utility model.As follow-up work, it remains interesting to enhance theconvergence performance of the proposed slicing strategyoptimizer with advanced operations and techniques in geneticsearch, such as fitness scaling, diploid evolution and sequencereordering.Especially, it worths an attempt to amelioratethe rate of convergence of GA with heuristic searching in order to meet the real-time requirementof network resource management. Besides, there is also a great potential to combine our genetic slicing strategy optimizer with other machine learningapproaches such as reinforcement learning and artificialneural networks.

ADVANTAGES

  • Exhibiting a satisfying approximate to the global optimum,
  • A fast convergence,
  • A timely adaptation to environment variation and a good scalability.
  • Good robustness against non-stationary service scenarios.

 BLOCK DIAGRAM

 DESCRIPTION

The proposed method is highly abstracted definition of resource for keeping the generality. In practice,network slicing can be applied both on physical resources,i.e. radio/infrastructure resources, and on virtualizedresource blocks, i.e. computational capacity. The practical design of resource pool, therefore, depends on the usecase specification. Generally, all virtualized resource blockson the same server or server cluster, no matter exploited bywhich virtual network function (VNF), can be consideredas homogeneous and therefore modeled with one dimension of the resource vector r. In contrast, heterogeneousphysical resources such as frequency bands and transmission power, must be distinguished with different orthogonaldimensions in r.The linear resource assignment formally excludes any resource multiplexing overdifferent slices, which is,especially for physical resources,not only common in practice but also essential for realizingslice elasticity. Nevertheless, in the contextof inter-slice resource management, an elastic slice thatshares resources with other homogeneous slices is equivalentin resource consumption to an inelastic slice with downscaledutility efficiency.

SYSTEM  IMPLEMENTATION

Tool                               :         MATLAB 8.1

Platform                         :         Windows/linux

Scripting Language        :         C / Matlab coding

 

REFERENCE:

BIN HAN and JI LIANGHAI, “Slice as an Evolutionary Service: GeneticOptimization for Inter-Slice ResourceManagement in 5G Networks”IEEE Acess June 8, 2018.

Sensitive and Nonlinear Far Field RF Energy Harvesting in Wireless Communications

Sensitive and Nonlinear Far Field RF Energy Harvesting in Wireless Communications

ABSTRACT

RF harvester’s sensitivity may be several dBs worse than communications receiver’s sensitivity, potentially rendering RF information signals useless for energy harvesting purposes. Given finite number of datapoint pairs of harvested (output) power and corresponding input power, a piecewise linear approximation is applied and the statistics of the harvested power are offered, as a function of the wireless channel fading statistics. Limited number of datapoints are needed and accuracy analysis is also provided. Case studies include duty-cycled (non-continuous), as well as continuous SWIPT, comparing with industry-level, RF harvesting. The proposed approximation, even though simple, offers accurate performance for all studied metrics. On the other hand, linear models or nonlinear-unlimited sensitivity harvesting models deviate from reality, especially in the low-input-power regime..

 INTRODUCTION

Far field radio frequency (RF) energy harvesting, i.e., the capability of wireless nodes to scavenge energy, either from remote ambient or dedicated RF sources, has recently attracted significant attention. Compared to other energy harvesting methods, e.g., from motion, sun or heat, RF energy harvesting offers the advantage of simultaneous wireless information and power transfer (SWIPT). The latter lies at the heart of the radio frequency identification (RFID) industry, which is expected to drive research and innovation in a plethora of coming Internetof- Things (IoT) scenarios and low-power applications . Recent SWIPT literature within the wireless communications theory research community has addressed problems relevant to protocol architecture, as well as fundamental performance metrics. Several motivating examples demonstrating the concept of SWIPT exist in the literature, e.g., for memoryless point-to-point channels , frequency-selective channels , multiple-input multiple-output (MIMO) broadcasting, and relaying ..

EXISTING SYSTEM:

Huang and E. Larsson, “Simultaneous information and power transfer for broadband wireless systems,” IEEE Trans. Signal Process., vol. 61, no. 23, pp. 5972–5986, Dec. 2013.

Wireless power transfer in wireless communications imposes additional energy harvesting constraints

Krikidis, S. Timotheou, S. Nikolaou, G. Zheng, D. W. K. Ng, and R. Schober, “Simultaneous wireless information and power transfer in modern communication systems,” IEEE Commun. Mag., vol. 52, no. 11, pp. 104–110, Nov. 2014

The current perspective of linear RF harvesting within the wireless communications theory community.

 PROPOSED SYSTEM:

The proposed approximation methodology offers exact performance for all studied metrics. In addition, no tuning of any parameter is required. On the other hand, linear RF harvesting modeling results deviate from reality, and in some cases are off by one order of magnitude, while nonlinear RF harvesting models from recent prior art, that do not take into account limited harvesting sensitivity, deviate from reality in the low-input-power regime.The proposed methodology can be applied to any type of RF energy harvesting system, provided that systemlevel datapoint pairs of the harvested output power and the input power are provided. In that way, accurate SWIPT analysis can be facilitated..

ADVANTAGES

  • RF energy harvesting literature, realistic efficiency models ,sensitivity, nonlinearity, and saturation of the RF harvesting circuits.
  • Apiecewise linear approximation model is proposed, amenable to closed-form, tuning-free modeling, and expressions.
  • two real rectenna models from RF harvesting circuits’ prior art
  • It is deduced that the SWIPT research should take into account the nonlinearity of the actual harvesting efficiency and the limited sensitivity of the harvester.

BLOCK DIAGRAM

DESCRIPTION

A source of RF signals offers wireless power to an information and far field RF energy harvesting (IEH) terminal. The source of RF signals is assumed with a dedicated power source, while the far field IEH terminal harvests RF energy from the incident signals on its antenna and could operate as information transmitter or receiver. Narrowband transmissions are considered over a quasi-static flat fading channel. For a single channel use, the downlink received signal at the output of the matched filter at the IEH terminal is given by:

SYSTEM  IMPLEMENTATION

 Tool                               :         MATLAB 8.1

Platform                         :         Windows/linux

Scripting Language        :         C / Matlab coding

 REFERENCE:

Panos N. Alevizos, Student Member, IEEE and Aggelos Bletsas, Senior Member, IEEE, “Sensitive and Nonlinear Far Field RF EnergyHarvesting in Wireless Communications”, IEEETransactions on Wireless Communications, 2018.

 

Secret Key Establishment via RSS TrajectoryMatching Between Wearable Devices

Secret Key Establishment via RSS TrajectoryMatching Between Wearable Devices

ABSTRACT

Recently, people have witnessed a remarkable growth in the number of smart wearable devices. Accompanied with the development of a contactless data transmission technique, the lack of effective secret key establishment between lightweight wearable devices which support contactless data transmission technique becomes a security bottleneck. In thispaper, we propose a novel wireless key establishment method by moving or shaking the wearable wireless devices. Instead of received signal strength (RSS) itself, we denote the RSS trajectories of two moving wireless devices as the materials of secret key. Moreover, inspired by channel reciprocity in a channel feature-based key establishment technique, we propose the concept of reciprocity of RSS trajectory that guarantees that even when the RSSs of two devices are the same, the identical RSS trajectories of two devices can successfully generate the secret key. In addition, to effectively utilize the RSS trajectories, we design a novel quantization scheme by considering the entropy and efficiency of key generation. Furthermore, we analyze the security of this key establishment procedure in an eavesdropped and monitored environment. We also perform an evaluation of 64-, 128-, 192-, and 256-b key generation in indoor/outdoor environment, and the results indicate that the times are 0.22/0.33, 0.61/0.74, 0.95/1.02, and 1.28/1.46 s, respectively. In addition, the ranges of efficiency and entropy are 0.654–0.795 and 0.968–0.993.

INTRODUCTION

Earable devices equipped with sensors have been one of the remarkable outcomes in people’s dailylife over the past 10 years. These smart, wearable devicesare gaining popularity and becoming an important part ofe-healthcare, sports and fitness applications. The deviceslike FitBit Flex, Nike+ Fuel band measure the person’sphysiological data, monitor activity and sleep quality, andsync wirelessly to the personal devices/base station (BS).
The BS can then upload this data to a cloud based database to facilitate access by the hospital authority or caretakersfor timely treatment. The lightweight, resource constrainedwearable devices communicate with each other by usingWi-Fi, Blue tooth, UWB or other short range communicationtechnologies. Wireless channels, upon which information istransmitted from one device to another, are public and canbe accessed by wireless devices without authorization. Thisnature of wireless communications results in private information collected by wearable devices being transferred publicly,providing a potentially lucrative attack space. For instance,eavesdropping of confidential data and injection of maliciouscommands which can cause adverse effects on a person’shealth. Since these wearable devices handle sensitive healthinformation, securing the information is crucial to ensuretrustworthy and usable wireless communication.

EXISTING SYSTEM:

Xi et al., “Instant and robust authentication and key agreement amongmobile devices,” in Proc. ACM SIGSAC Conf. Comput. Commun. Secur.,2016, pp. 616–627.

Channel phase and channel impulse response (CIR) are typical physical layer characteristics regarded assuccessful metrics to share keys between communicationentities.

Wang et al., “Walls have ears! Opportunistically communicatingsecret messages over the wiretap channel: From theory to practice,”in Proc. 22nd ACM SIGSAC Conf. Comput. Commun. Secur., 2015,pp. 376–387

Presents a practical opportunistic secret communication system, letting the legitimate sender communicate secret messages right away over wireless channels under the wiretap channel model. These methods establish a shared key between Alice and Bob by exploiting wireless channel reciprocity property, which states that a transmitter and a receiver observe the same channel characteristics (e.g., RSS, CIR, etc.) from the wireless link between them at the same time.

 PROPOSED SYSTEM:

The proposed method presents a new key establishment method that is independent of channel selections and supports multiplex communication to enable Alice and Bob to capture common trajectory features simultaneously. Alice and Bob can send radio signals over two different frequency channels at the same time. Both frequency channels will exhibit the same trajectory feature, i.e., decreasing RSS when they move apart and increasing RSS when then they move close. The proposed method, combining these two kinds of techniques together in some way, is a new method to get the advantages: richer source information from CIR-based methods and low computational overhead from RSS-based methods.  Once the devices sample the received signals and calculate the RSS trajectories, the designed mean-value quantization scheme is used to parse the RSS trajectories into bit sequences. Because of the complex wireless environment and other interferences (i.e. random noise), detail an error correction scheme to correct the mismatch bits and enhance the security.

Advantages

  • Richer source information from CIR-based methods
  • Low computational overhead from RSS-based methods.

BLOCK DIAGRAM

DESCRIPTION

The main contribution of this project is three-fold. Firstly, Propose the concept of RSS trajectory reciprocity, where the RSS measurements of two devices have the same fluctuations as they are moved relative to each other. Secondly, a novel key establishment technique for pairs of devices is presented, which functions of the movement of both and a “virtual” full-duplex mode. This method could obtain high efficiency with a relative low cost. Then,  offer a lemma analyzing and proving the rationality and demonstrate its efficacy in generating secret keys. Thirdly, design a novel mean-value quantization scheme to facilitate key generation, which divides the collection of samples into several sub-sequences instead of directly quantizing the sample values one by one. Two sub-sequence division methods are proposed. Finally,  analyze the security of our key establishment technique and prove that it can defend against eavesdropping because of the unpredictable RSS trajectories involved.

SYSTEM  IMPLEMENTATION

Tool                               :         MATLAB 8.1

Platform                         :         Windows/linux

Scripting Language        :         C / Matlab coding

 

REFERENCE

YINAN TANG and HONGXIANG GUO, “Secret Key Establishment via RSS TrajectoryMatching Between Wearable Devices”, IEEE Access February 12, 2018.

 

Relay Hybrid Precoding Design in Millimeter-Wave Massive MIMO Systems

Relay Hybrid Precoding Design in Millimeter-Wave Massive MIMO Systems

ABSTRACT

We propose an iterative successive approximation (ISA) algorithm to attain the high-approximate optimal solution to the original problem. Specifically, in the proposed ISA algorithm, we first convert the two nonconvex subproblems to convex ones by the relaxation of the constant-modulus constraints, and then we solve the three corresponding convex subproblems iteratively.We theoretically prove that the ISA algorithm converges to a Karush–Kuhn–Tucker point of the original problem.

INTRODUCTION

AS A promising technology for the next generation of wireless communications, millimeter-wave (mmWave) communication has drawn extensive research interests in the recent years.By utilizing large spectrum bands between 30GHz and 300 GHz, mmWave communication is capable of meeting the explosive growth of data rate. Although themmWave signals undergo severe path loss, the path loss can be compensated by high antenna gain using massive multiple-input multipleoutput (MIMO). However, mmWave communications are mainly applied in line-of-sight (LoS) dominant scenarios, since mmWave signals are sensitive to blockage. To mitigate the negative effects caused by blockage, relay can be employed in mmWave massive MIMO systems . In a relay-assisted mmWave system, the channels from the source to the relay and from the relay to the destination may be LoS, and the transmission range and coverage can be extended. Similar to the conventional mmWave massive MIMO system, precoding plays an important role  in the relay-assisted mmWave massive MIMO system to compensate for the high path loss by the high antenna gain . However, the optimal precoding design for the relay-assisted mmWave massive MIMO systems is a challenging problem due to the complicated signal processing.

EXISTING SYSTEM:

Gao, L. Dai, S. Han, C.-L. I, and X.Wang, “Reliable beamspace channel estimation for millimeter-wave massive MIMO systems with lens antenna array,” IEEE Trans. Wireless Commun., vol. 16, no. 19, pp. 6010–6021, Sep. 2017.

The recently proposed hybrid (analog/digital) precoding is a more attractive alternative, since it achieves the similar performance to the full digital one with much fewer RF chains.

 E. Ayach, S. Rajagopal, S. Abu-Surra, Z. Pi, and R. W. Heath, “Spatially sparse precoding in millimeter wave MIMO systems,” IEEE Trans. Wireless Commun., vol. 13, no. 3, pp. 1499–1513, Mar. 2014.

The hybrid precoding is jointly realized in the digital and analog domains, where the digital precoding is realized by baseband signal processing, while the analog precoding is usually implemented by analog phase shifters

 PROPOSED SYSTEM:

we propose a minimum mean squared error (MMSE)-based relay hybrid precoding design. This challenging problem is highly non-convex due to the six-order polynomial objective function, sixorder polynomial constraint, block-diagonal constraints, and constant-modulus constraints. To eliminate the blockdiagonal constraints and reduce the problem dimension, we reformulate the original problem as three subproblems. Here, one of these three subproblems is a convex quadratically constrained quadratic programming (QCQP) problem, while the other two subproblems are non-convex QCQP problems with constant-modulus constraints. To solve these three subproblems, we propose an iterative successive approximation (ISA) algorithm with affordable complexity. In the proposed ISA algorithm, we first derive the closed-form solution to the convex QCQP subproblem. Then, for the two non-convex QCQP subproblems, we convert them to be convex by the relaxation of the constant-modulus constraints. Then, the high-approximate solution is obtained by iteratively solving these three convex problems.

 ADVANTAGES

  • Efficient SC designs, namely, SC-DRS for global full CSI feedback and SC-LFu for local full CSI feedback, and SC-LQu for local quantized CSI feedback, which significantly reduce the channel estimation overhead of the FMA-WBSN.
  • Global full CSI feedback that enable effective mitigation of the inter-SC interference
  • The number of antennas at the MBS increases and the cross-access link signal power becomes smaller

BLOCK DIAGRAM

SYSTEM MODEL

This section briefly introduces the mmWave channel model and the relay hybrid precoding system model with both subconnected and full-connected structures.

  1. Millimeter-Wave Channel Model

As shown in Figs. 1 and 2, we consider an amplify-andforward (AF) relay assisted mmWave massive MIMO system without direct link between the source and the destination.1 As can be seen, the considered system includes the channels H from the source to the relay, and G from the destination to the relay. Here, we assume that the channels H and G are LoS. , the propagation loss of the LoS channels H and G obeys the Rician distribution. In this paper, we consider the narrowband mmWave channel model widely used in the literatures . The more challenging optimal design of the relay hybrid precoding over “delay-d” widebandmmWave channels is beyond the scope of the current paper and will be studied in our future work. Due to the fact thatmmWave channels exhibit limited number of paths ,HandGoften have sparse structures, which can be characterized by low-rank matrices as follows:

Relay Hybrid Precoding

For both the full-connected and the sub-connected structures as shown in Figs. 1 and 2, the relay employs the hybrid precoding, where K RF chains and MR antennas are used. The difference between these two structures is that, the kth (k = 1, 2, . . .,K) RF chain is connected to a subset of MR k antennas in the sub-connected structure, while the kth (k = 1, 2, . . . , K) RF chain is connected to all MR antennas in the full-connected structure.

SYSTEM  IMPLEMENTATION

 Tool                               :         MATLAB 8.1

Platform                         :         Windows/linux

Scripting Language        :         C / Matlab coding

 REFERENCE:

Xuan Xue, Student Member, IEEE, Yongchao Wang, Member, IEEE, Linglong Dai, Senior Member, IEEE,Christos Masouros, Senior Member, IEEE, “Relay Hybrid Precoding Design in Millimeter-WaveMassive MIMO Systems”, IEEE

Transactions on Signal Processing, 2018.