Multi-user Multi-input Multi-output Research Articles

Wireless Powered Information Transfer Based on Zero-Forcing for Multiuser MIMO Systems

A zero-forcing (ZF)-based transmission method is proposed for a wireless powered communication network (WPCN) with multiuser multi-input multi-output (MU-MIMO) channels. We formulate the max–min user rate optimization problem based on ZF-based uplink transmission, under the transmit power constraints determined by the downlink power transfer, and derive a Newton-like iterative algorithm to find the optimal solution of the proposed problem. Using the proposed ZF-based method, we design a downlink energy beamformer, and optimize the uplink power allocation vector, precoder, and combiner in terms of the max–min user rate for a MU-MIMO WPCN system. Numerical simulations show that the proposed method provides at least 3 dB signal-to-noise ratio gain compared to the conventional transmission schemes for WPCN. Moreover, through complexity analysis and simulations, it is shown that the proposed method can reduce at least 92% of the computation load in terms of runtime with moderate achievable rate loss, compared to the optimal method obtained by the interior-point method.

Low-Complexity Multiuser MIMO Precoder Design Under Per-Antenna Power Constraints

A new precoder design method is proposed for multi-input multioutput (MIMO) systems with per-antenna power constraints (PAPCs). In the proposed scheme, the optimal zero-forcing (ZF) based precoder maximizing the sum rate is evaluated for MIMO systems under the conventional sum power constraint (SPC), after which a new ZF-based precoder conforming to the PAPCs is designed by finding the linear precoder closest to the optimal ZF-based SPC precoder. Using the proposed design procedure, we derive an iterative algorithm based on the modified Newton's method to construct a PAPC precoder for a multiuser MIMO system. The complexity order of the proposed method is compared with those of the existing precoding schemes, and it is shown through numerical simulations that the proposed PAPC precoder achieves near-optimal performance while reducing the power consumption at macrocell base stations.

Wireless energy transfer in downlink and wireless communications in uplink for multi-user MIMO networks

In this paper, the energy is wireless transferred in the multi-user multi-input multi-output (MU-MIMO) broadcast channel and the information is wireless transmitted in the MAC MU-MIMO channel. The energy efficiency metric and the spectral efficiency objective are theoretically traded off for the wireless energy and information transmission networks, which results in the analytical expression. Moreover, the number of the transmit antennas and that of the mobile terminals are optimized to the closed form expression by maximizing the energy efficiency with the quality of service (QoS) in terms of the required spectral efficiency. Finally, the optimal energy efficiency of the whole networks is obtained with the optimized number of both antennas and mobile terminals. The key feature of this paper is the analytical expression of the power allocation for the best energy efficiency. Numerical simulations demonstrate the effectiveness of the proposed method for the MU-MIMO wireless energy and information transmission networks.

Leakage-based precoding algorithms for multiple streams per terminal MU-MIMO systems

Mobile networks rely extensively on multi-input multi-output (MIMO) communications to increase the data rate and improve signal quality. In multi-user MIMO (MU-MIMO) the signals are steered at the base station, forming multiple beams to the several user terminals (UTs). This is achieved by precoding the signals to be sent to the UTs. In leakage-based precoding, the precoding vectors are selected so that the signal to leakage plus noise ratio is maximized, where leakage is the amount of signal that is meant for a given UT but is received by the other UTs. This technique gives better results than techniques that completely eliminate the interference without regard to the signal or noise level (zero forcing solutions) like the block diagonal (BD) algorithm. However, current leakage-based algorithms are only optimal in the case of single-antenna UTs. In this paper, we propose simplified versions of these algorithms suitable for multiple streams per UTs, and compare its performance with existing solutions. Simulation results show an increase in performance. One of the versions does not require any Singular Value Decomposition (SVD) while the other does SVD of a much smaller matrix. Both still achieve better performance than the competition.

Full-duplex Distributed Massive MIMO System with Optimal Beamforming and Resource Allocation for WPCN

This paper proposes a joint beamforming and resource allocation scheme to maximize the minimum capacity for wireless powered communication network (WPCN) designed for multi-user distributed massive multi-input multi-output (DM-MIMO) system with full-duplex radio remote heads (RRHs), which enable simultaneous uplink (UL) and downlink (DL) communications. The minimum capacity is maximized by a proposed algorithm based on the non-negative matrix theory. The simulation results have demonstrated that the achievable max-min capacity of the DM-MIMO is considerably higher compared to that of the CMMIMO system. It has also showed that the convergence speed of the proposed algorithm is so fast.

Interference suppression algorithm based R-TDD for multi-user MIMO heterogeneous network

Aiming at the problem of uplink co-channel interference in multi-user multi-input multi-output (MIMO) heterogeneous network, a reversed time division duplex (R-TDD)-based method is used to improve the performance of interference rejection combining (IRC) algorithm. This method overcomes the difficulty of IRC algorithm in obtaining the interference noise covariance matrix by utilizing the R-TDD transmission scheme. On the premise that the spectrum efficiency is guaranteed, through combining R-TDD with spatial modulation, the transmission complexity is significantly reduced and the uplink co-channel interference is effectively controlled, so as to improve the system performance. Simulation results demonstrate that the R-TDD-based scheme can improve the performance of IRC algorithm in terms of spectrum efficiency.

Max–min fairness based linear transceiver–relay design for MIMO interference relay channel

In this work, the authors investigate a multi-user multi-input multi-output (MIMO) interference relay system, where several transmitter nodes simultaneously communicate with their respective receiver nodes through half-duplex MIMO amplify and forward (AF) relay nodes. For this system configuration, they address the problem of linear transceiver–relay design to achieve max–min fairness among all the users' data streams. Assuming perfect channel state information, this problem is formulated as the maximisation of the minimum signal-to-interference-plus-noise ratio (SINR) per stream among all the users subject to transmit power constraints at the transmitter and relay nodes. Since the formulated problem of jointly optimising all the transmitters, relays and receivers is non-convex, a globally optimal solution cannot be easily obtained. Therefore, they propose a quasi-optimal iterative algorithm to jointly optimise the transmitter precoders, relay precoding matrices and receiver filters for all the users and relays such that the minimum per stream received SINR is improved at each iteration. Simulation results show that the proposed algorithm improves fairness among data-streams of all users and outperforms existing strategies in terms of minimum user rate and bit error rate.

Massive MIMO Channel Subspace Estimation From Low-Dimensional Projections

Massive MIMO is a variant of multiuser MIMO (Multi-Input Multi-Output) system, where the number of base-station antennas $M$ is very large and generally much larger than the number of spatially multiplexed data streams. Unfortunately, the front-end A/D conversion necessary to drive hundreds of antennas, with a signal bandwidth of 10 to 100 MHz, requires very large sampling bit-rate and power consumption. To reduce complexity, Hybrid Digital-Analog architectures have been proposed. Our work in this paper is motivated by one of such schemes named Joint Spatial Division and Multiplexing (JSDM), where the downlink precoder (resp., uplink linear receiver) is split into product of a baseband linear projection (digital) and an RF reconfigurable beamforming network (analog), such that only $m \ll M$ A/D converters and RF chains is needed. In JSDM, users are grouped according to similarity of their signal subspaces, and these groups are separated by the analog beamforming stage. Further multiplexing gain in each group is achieved using the digital precoder. Therefore, it is apparent that extracting the signal subspace of the $M$ -dim channel vectors from snapshots of $m$ -dim projections , with $m \ll M$ , plays a fundamental role in JSDM implementation. In this paper, we develop efficient subspace estimation algorithms that require sampling only $m=O(2 \sqrt{M})$ antennas and, for a given $p \ll M$ , return a $p$ -dim beamformer (subspace) that has a performance comparable with the best $p$ -dim beamformer designed from the full knowledge of the exact channel covariance matrix. We assess the performance of our proposed estimators both analytically and empirically via numerical simulations.

Precoding Design for Multiuser MIMO Downlink Communication Systems Using an LQ-Based Cascade GSIC Algorithm

This paper proposes a novel LQ-based generalized side-information cancellation (GSIC) precoder for multiuser multi-input multi-output (MU-MIMO) downlink systems with sum-rate performance enhancement. The proposed transceiver comprises the following stages. First, a unitary transform matrix designed through the LQ decomposition of the MU-MIMO channel is proposed for suppressing MU interference and obtaining the low-triangular MU-MIMO channel effect for each receiving user. A subchannel matrix with a nontriangular channel causes interference from other users to degrade the reception performance for each user. To overcome this problem, we propose a novel cancellation matrix for suppressing nontriangular MU-MIMO channel and composite noise effects. The proposed LQ-based precoder scheme, which is coupled with unitary transformation and cancellation matrices, can be extended for use with multiple users. The LQ-based GSIC precoder for two users can be realized and extended to three or more users by adopting a cascaded structure. The closed-form solution of the proposed LQ-based GSIC precoder is derived using a constraint-based optimization algorithm. Furthermore, suboptimum solutions show that the performance of the proposed GSIC precoder is almost equal to that of the optimum solutions, and that the precoder also has low complexity. Simulation results show that the proposed LQ-based GSIC precoder outperforms conventional precoders and exhibits reliable and excellent sum-rate performance.

Successive Convex Quadratic Programming for Quality-of-Service Management in Full-Duplex MU-MIMO Multicell Networks

This paper designs jointly optimal linear precoders for both base stations (BSs) and users in a multiuser multi-input multi-output (MU-MIMO) multicell network. The BSs are full-duplexing transceivers while uplink users and downlink users (DLUs) are equipped with multiple antennas. Here, the network quality-of-service (QoS) requirement is expressed in terms of the minimum throughput at the BSs and DLUs. We consider the problems of either QoS-constrained sum throughput maximization or minimum cell throughput maximization. Due to the nonconcavity of the throughput functions, the optimal solutions of these two problems remain unknown in both half-duplexing and full-duplexing networks. The first problem has a nonconcave objective and a nonconvex feasible set, whereas the second problem has a nonconcave and nonsmooth objective. To solve such challenging optimization problems, we develop iterative low-complexity algorithms that only invoke one simple convex quadratic program at each iteration. Since the objective value is proved to iteratively increase, our path-following algorithms converge at least to the local optimum of the original nonconvex problems. Due to their guaranteed convergence, simple implementation, and low complexity, the devised algorithms lend themselves to practical precoder designs for large-scale full-duplex MU-MIMO multicell networks. Numerical results demonstrate the advantages of our successive convex quadratic programming framework over existing solutions.

Wideband Directional Channel Characterization for Multiuser MIMO Systems Over a Random Rough Dielectric Ground

In this study, small perturbation method (SPM) and Kirchhoff approximation (KA) are incorporated into ray-tracing (RT) routines to model multiuser multi-input multi-output (MU-MIMO) channels formed on a rough dielectric terrain. The effect of surface roughness and correlation length, solid soil fractions, moisture content, link range, antenna height, polarization, radiation pattern, and carrier frequency are examined on received power, power delay and angular profiles, root mean square (RMS) delay and angular spread, coherence bandwidth, and coherence distance. Quantitative and qualitative analyses reveal that antenna directionality and terrain undulation and textural composition have significant impacts on the received signal power and channel multipath parameters and, hence, the performance of MU-MIMO terrain-based communication systems.

Resource allocation based on cross-layer QoS-guaranteed scheduling for multi-service multi-user MIMO–OFDMA systems

Cross-layer strategies for resource allocation in wireless networks are essential to guaranty an efficient utilization of the scarce resource. In this paper, we present an efficient radio resource allocation scheme based on PHY/MAC cross layer design and QoS-guaranteed scheduling for multi-user (MU), multi-service (MS), multi-input multi-output (MIMO) concept, orthogonal frequency division multiple access (OFDMA) systems. It is about a downlink multimedia transmission chain in which the available resources as power and bandwidth, are dynamically allocated according to the system parameters. Among these parameters, we can mention the physical link elements such as channel state information, spectral efficiency and error code corrector rate, and MAC link variables, which correspond to the users QoS requirements and the queue status. Primarily, we use a jointly method which parametrizes these system parameters, according to the total power, and the bit error rate constraints. Secondly, we propose a QoS-guaranteed scheduling that shares the sub-carriers to the users. These users request several type of traffic under throughput threshold constraints. The main objective in this work is to adjust the average throughput per service of each user, according to their needs and likewise to satisfy a great number of connexions. Subsequently, we consider a model of moderated compartmentalization between various classes of services by partitioning the total bandwidth into several parts. Each class of service will occupy a part of the bandwidth and will be transmitted over a maximum number of sub-carriers. The simulation results show that the proposed strategy provides a more interesting performance improvement (in terms of average data rate and user satisfaction) than other existing resource allocation schemes, such as nonadaptive resource allocation strategy. The performances are also analyzed and compared for the two multi-service multi-user MIMO---OFDMA systems; with sub-carriers partitioning and without sub-carriers partitioning.

Lattice reduction aided with block diagonalization for multiuser MIMO systems

The block diagonalization (BD) precoding technique is a well-known linear transmit strategy for multiuser multi-input multi-output (MU-MIMO) systems. The MU-MIMO broadcast channel is decomposed into multiple independent parallel single user MIMO (SU-MIMO) channels and achieves the maximum diversity order at high data rates. The lattice reduction-aided decoding (LRAD) features the reduced decoding complexity in MIMO communications. The Lenstra-Lenstra-Lovasz (LLL) algorithm has been extensively used to obtain better bases of the channel matrix while the complex lattice reduction (CLR) is aimed at improving orthogonality of basis vectors and shortening them. The orthogonalization and size reduction work are left for the CLR algorithm so that a modification of the channel matrix is carried out, resulting in better precoding and detection performances. We also derive bounds for lattice decoding. Simulation results show that the bit error rate (BER) performance of our proposed algorithm is better than that of conventional ones and it reduces the complexity compared with the LLL algorithm-based schemes.

Multi-Parameter Based Scheduling for Multi-user MIMO Systems

Multi-user multi-input multi-output (MU-MIMO) system has attracted the 4 th generation wireless network as one of core technique for performance enrichment. In this system rate control is a challenging problem and another problem is optimization. Proper scheduling can resolve these problems by deciding which set of user and at which rate the users send their data. This paper proposes a new multi-parameter based scheduling (MPS) for downlink multi-user multiple-input multiple-output (MU-MIMO) system under space-time block coding (STBC) transmissions. Goal of this MPS scheme is to offer improved link level performance in terms of a low average bit error rate (BER), high packet delivery ratio (PDR) with improved resource utilization and service fairness among the user. This scheme allows the set of users to send data based on their channel quality and their demand rates. Simulation compares the MPS performance with other scheduling scheme such as fair scheduling (FS), normalized priority scheduling (NPS) and threshold based fair scheduling (TFS). The results obtained prove that MPS has significant improvement in average BER performance with improved resource utilization and fairness as compared to the other scheduling scheme.

User scheduling for MU-MIMO transmission with active CSI feedback

User scheduling boosts the multi-user multi-input multi-output (MU-MIMO) gain by selecting an optimal set of users to increase the 802.11 Wi-Fi system capacities. Many kinds of user scheduling algorithms, however, fail to fully realize the advantages of MU-MIMO due to considerable channel state information (CSI) overhead. In this paper, we propose a new MU-MIMO MAC protocol, called 802.11ac+, including a novel user scheduling algorithm. Unlike most proposals, where user scheduling is performed after an access point (AP) receives CSI from all users, 802.11ac+ determines the best user set during the CSI feedback phase. In particular, the AP broadcasts a channel hint about previously scheduled users, and the remaining users actively send CSI reports according to their effective channel gains (ECGs) calculated from the hint. Based on the proposed scheme, we develop two fair scheduling protocols, Round-Robin 802.11ac+ (RR-11ac+) and Proportional-Fair 802.11ac+ (PF-11ac+). Through trace-driven MATLAB simulations, we prove that the proposed schemes not only improve the throughput gain but also enhance the fairness among users.

A simple block diagonal precoding for multi-user MIMO broadcast channels

Abstract The block diagonalization (BD) is a linear precoding technique for multi-user multi-input multi-output (MIMO) broadcast channels, which is able to completely eliminate the multi-user interference (MUI), but it is not computationally efficient. In this paper, we propose the block diagonal Jacket matrix decomposition, which is able not only to extend the conventional block diagonal channel decomposition but also to achieve the MIMO broadcast channel capacity. We also prove that the QR algorithm achieves the same sum rate as that of the conventional BD scheme. The complexity analysis shows that our proposal is more efficient than the conventional BD method in terms of the number of the required computation.

Channel Quantization Using Constellation Based Codebooks for Multiuser MIMO-OFDM

In this paper, we propose clustered quantization techniques for multiuser multi-input/multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) using constellation based codebooks. Constellation based codebooks provide scalability and efficient codeword search capability, which are key features for practical multiuser MIMO-OFDM systems with a large number of antennas. The proposed clustered quantization scheme quantizes consecutive subcarriers into a single codeword that minimizes aggregated quantization errors. We base our new clustering techniques on two constellation based quantization methods, namely equal-magnitude angular quantization (EMAQ) and squared-lattice angular quantization. New efficient codebook search algorithms are proposed for the clustered quantization. In addition, we propose new constellations to guarantee different users quantize channels into distinct codewords. One is a rotated M-PSK constellation suitable for randomly-distributed user scenarios, and the other is a random phase equal-magnitude (RPEM) constellation suitable for ill-conditioned user scenarios. Thus, full spatial multiplexing gain can be achievable even with small number of users. Finally, a near-sphere codeword search algorithm is proposed for the RPEM. In simulations, the proposed clustered quantization shows up to 50% higher throughput compared to conventional fixed-pilot channel quantization. Also, we show our new constellations for EMAQ improve throughput almost 35% compared to the standard EMAQ.

Multi-user selection based on particle swarm optimization and power control scheme in the uplink CoMP-MU-MIMO system

Orthogonal frequency division multiplexing (OFDM) which has been adopted in the long-term evolution (LTE) system can improve the system capacity obviously. However, it also brings about severe inter-cell interference (ICI) for cell-edge users (CEUs). To tackle this problem, multi-user selection and power control (MuS-PC) is proposed as an efficient scheme in uplink coordinated multi-point multi-user multi-input multi-output (CoMP-MU-MIMO) transmission/reception. This paper jointly considers user's signal to interference plus noise ratio (SINR) and proportional fairness (PF) to maximize the total channel capacity in multi-user selection by formulating a penalty function. To simplify the penalty function's computation, particle swarm optimization (PSO) algorithm is introduced. In addition, power control is adopted to maximize overall energy efficiency. Simulation results demonstrate that the MuS-PC scheme can not only obtain the optimal total channel capacity while guarantee each user's quality of service (QoS) and PF, but also largely reduce computational complexity and improve energy efficiency. As a result, the poor communication quality of CEUs can be enhanced.

Max-Min Fairness Linear Transceiver Design for a Multi-User MIMO Interference Channel

Consider the max-min fairness linear transceiver design problem for a multi-user multi-input multi-output (MIMO) interference channel. When the channel knowledge is perfectly known, this problem can be formulated as the maximization of the minimum signal-to-interference-plus-noise ratio (SINR) utility, subject to individual power constraints at each transmitter. We prove in this paper that, if the number of antennas is at least two at each transmitter (receiver) and is at least three at each receiver (transmitter), the max-min fairness linear transceiver design problem is computationally intractable as the number of users becomes large. In fact, even the problem of checking the feasibility of a given set of target SINR levels is strongly NP-hard. We then propose two iterative algorithms to solve the max-min fairness linear transceiver design problem. The transceivers generated by these algorithms monotonically improve the min-rate utility and are guaranteed to converge to a stationary solution. The efficiency and performance of the proposed algorithms compare favorably with solutions obtained from the channel matched beamforming or the leakage interference minimization.

간섭 제거와 수신 성능 향상을 위한 전처리기법을 적용한 LDC기반의 다중 사용자 다중 입출력 시스템

본 논문에서는 다중사용자 다중입출력 시스템에서 대역폭 효율의 감소 없이 페이딩에 대한 수신 성능을 향상시키는 부호화 알고리듬을 제안한다. 기존의 다중사용자 다중입출력 방식으로 사용되는 공간분할다중화 방식은 페이딩 경로에 취약하며, 이를 극복하기 위한 시공간블록부호화 방식은 전송량이 떨어지는 단점이 있다. 이러한 문제점을 개선하기 위하여 제안 부호화 알고리듬은 페이딩 환경에 강인하고 전송량이 송신 안테나 개수에 비례하여 증가하는 LDC(linear dispersion code) 기법을 이용하여 송신 심벌을 부호화하고, 예측한 채널 이득의 특이값 분해 값을 LDC 부호화 심벌에 전처리하여 성능을 개선한다. 그리고 컴퓨터 모의실험을 통하여 기존 알고리듬과 제안하는 알고리듬의 성능을 비교 평가한다.