Outage Performance and Optimal Design of MIMO-NOMA Enhanced Small Cell Networks with Imperfect Channel-State Information

This paper focuses on boosting the performance of small cell networks(SCNs)by integrating multiple-input multiple-output(MIMO)and nonorthogonal multiple access(NOMA)in consideration of imperfect channel-state information(CSI).The estimation error and the spatial randomness of base stations(BSs)are characterized by using Kronecker model and Poisson point process(PPP),respectively.The outage probabilities of MIMO-NOMA enhanced SCNs are first derived in closed-form by taking into account two grouping policies,including random grouping and distance-based grouping.It is revealed that the average outage probabilities are irrelevant to the intensity of BSs in the interference-limited regime,while the outage performance deteriorates if the intensity is sufficiently low.Besides,as the channel uncertainty lessens,the asymptotic analyses manifest that the target rates must be restricted up to a bound to achieve an arbitrarily low outage probability in the absence of the inter-cell interference.Moreover,highly correlated estimation error ameliorates the outage performance under a low quality of CSI,otherwise it behaves oppositely.Afterwards,the goodput is maximized by choosing appropriate precoding matrix,receiver filters and transmission rates.In the end,the numerical results verify our analysis and corroborate the superiority of our proposed algorithm.

Study on Performance of Wireless Multihop Networks Using MIMO MRC and MIMO MRT

This paper presents the concepts of completely connected network,mean path length and cluster for analysis performance of wireless multihop network,where matrix are used to express topology of network and use a new algorithm to compute the number of cluster in the network.Multiple-input/multiple-output(MIMO) communication promises performance enhancement over conventional single-input/single-output(SISO) technology for the same radiated power,if leveraged in multihop network,MIMO may be able to provide significant network performance improvement in network robustness and in power consumption,this paper analyzes three types of multihop networks employing SISO, MIMO with maximum ratio combining(MRC) and MIMO with maximum ratio transmission(MRT) as link model respectively,and get that using MIMO link model can increase robust,decrease mean path length by simulation.

BLIND CHANNEL AND SYMBOL JOINT ESTIMATION IN COOPERATIVE MIMO FOR WIRELESS SENSOR NETWORK

In this paper,application of Sequential Quasi Monte Carlo(SQMC)to blind channel andsymbol joint estimation in cooperative Multiple-Input Multiple-Output(MIMO)system is proposed,which does not need to transmit training symbol and can save the power and channel bandwidth.Additionally,an improved version of SQMC algorithm by taking advantage of current received signal isdiscussed.Simulation results show that the SQMC method outperforms the Sequential Monte Carlo(SMC)methods,and the incorporation of current received signal improves the performance of theSQMC obviously.

OPTIMAL POWER ALLOCATION WITH AF AND SDF STRATEGIES IN DUAL-HOP COOPERATIVE MIMO NETWORKS

Dual-hop cooperative Multiple-Input Multiple-Output (MIMO) network with multi-relay cooperative communication is introduced. Power allocation problem with Amplify-and-Forward (AF) and Selective Decode-and-Forward (SDF) strategies in multi-node scenario are formulated and solved respectively. Optimal power allocation schemes that maximize system capacity with AF strategy are presented. In addition, optimal power allocation methods that minimize asymptotic Symbol Error Rate (SER) with SDF cooperative protocol in multi-node scenario are also proposed. Furthermore, performance comparisons are provided in terms of system capacity and approximate SER. Numerical and simulation results confirm our theoretical analysis. It is revealed that, maximum system capacity could be obtained when powers are allocated optimally with AF protocol, while minimization of system's SER could also be achieved with optimum power allocation in SDF strategy. In multi-node scenario, those optimal power allocation algorithms are superior to conventional equal power allocation schemes.

A NOVEL INDOOR GEO-LOCATION METHOD USING MIMO ARRAY

In a Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) based Wireless Local Area Network (WLAN) system, both Access Points (APs) and Mobile Termi-nals (MTs) are configured with multiple antennas, to make novel indoor geo-location method possible. In this paper, we presented a novel Least Square Support Vector Machine (LS-SVM) based data fusion algorithm to fuse signal strength measurements for indoor geo-location using only a single AP with MIMO arrays. We evaluate our proposed algorithms under indoor environments by MATLAB simulations. Simulation results show that our MIMO-based algorithm is superior to conventional least square algorithm.

Joint beamforming and scheduling in the downlink of cognitive radio networks

Cognitive radio has been recently proposed as a promising technology to improve the spectrum utilization. In this paper, we consider a system where a licensed radio spectrum is shared by a primary network and a secondary network. Based on the subspace theory, a novel low-complexity algorithm for secondary user selection has been proposed. On the basis of the scheduling scheme, we jointly consider transmit beamforming, scheduling and power allocation, and subsequently present a complete set of solution for secondary network downlink. Simulation results has shown that our proposed scheme not only can limit the introduced interference at primary users within the tolerable range, but also can achieve high sum-rate throughput of secondary network, simultaneously. Furthermore, as is proved by simulation results, our scheme is very robust due to the fact that only a little tolerable performance drop is introduced when simple but nonoptimal equal power allocation is adopted.

Embracing non-orthogonal multiple access in future wireless networks

This paper provides a comprehensive survey of the impact of the emerging communication technique, non-orthogonal multiple access （NOMA）, on future wireless networks. Particularly, how the NOMA principle affects the design of the generation multiple access techniques is introduced first. Then the applications of NOMA to other advanced communication techniques, such as wireless caching, multiple-input multiple-output techniques, millimeter-wave communications, and cooperative relaying, are discussed. The impact of NOMA on communication systems beyond cellular networks is also illustrated, through the examples of digital TV, satellite communications, vehicular networks, and visible light communications. Finally, the study is concluded with a discussion of important research challenges and promising future directions in NOMA.

Doubling Phase Shifters for Efficient Hybrid Precoder Design in Millimeter-Wave Communication Systems

Hybrid precoding is a cost-effective approach to support directional transmissions for millimeter-wave(mmWave)communications,but its precoder design is highly complicated.In this paper,we propose a new hybrid precoder implementation,namely the double phase shifter(DPS)implementation,which enables highly tractable hybrid precoder design.Efficient algorithms are then developed for two popular hybrid precoder structures,i.e.,the fully-and partially-connected structures.For the fully-connected one,the RF-only precoding and hybrid precoding problems are formulated as a least absolute shrinkage and selection operator problem and a low-rank matrix approximation problem,respectively.In this way,computationally efficient algorithms are provided to approach the performance of the fully digital one with a small number of radio frequency(RF)chains.On the other hand,the hybrid precoder design in the partially-connected structure is identified as an eigenvalue problem.To enhance the performance of this cost-effective structure,dynamic mapping from RF chains to antennas is further proposed,for which a greedy algorithm and a modified K-means algorithm are developed.Simulation results demonstrate the performance gains of the proposed hybrid precoding algorithms over existing ones.It shows that,with the proposed DPS implementation,the fully-connected structure enjoys both satisfactory performance and low design complexity while the partially-connected one serves as an economic solution with low hardware complexity.