New balanced linear transceiver designs for a MIMO interfering broadcast channel

In conventional cellular network systems, the cell edge users are vulnerable to interference from neighboring cells. In order to deal with this problem, coordinate multipoint transmission/reception(CoMP) has been proposed in LTE-A system. Yet, in recent years, multiuser multiple- input-multiple output (MU-MIMO) has been well developed. The MU-MIMO technique allows the simultaneous transmission of multiple user signals in the same time at the same frequency band, and hence enhances the system performance effectively. Thus, LTE-A tries to integrate MU-MIMO and CoMP hoping for better peak data rate and higher spectrum efficiency. This thesis aims to investigate intra-site MU CoMP joint processing (JP) techniques. We propose a new antenna-selection-based JP method that can better use the system resource and reduce the feedback overhead. Thanks to the antenna selection technique, we can translate a multipoint CoMP problem to a virtual single-point CoMP problem such that the existing single-point MU-MIMO technique can be directly applied. Numerical results show that the proposed method outperforms the conventional approach and at the same time requires less feedback overhead.

In this paper, we present robust joint non-linear transceiver designs for multiuser multiple-input multiple-output (MIMO) downlink in the presence of imperfections in the channel state information at the transmitter (CSIT). The base station (BS) is equipped with multiple transmit antennas, and each user terminal is equipped with one or more receive antennas. The BS employs Tomlinson-Harashima precoding (THP) for inter-user interference pre-cancellation at the transmitter. We consider robust transceiver designs that jointly optimize the transmit THP filters and receive filter for two models of CSIT errors. The first model is a stochastic error (SE) model, where the CSIT error is Gaussian-distributed. This model is applicable when the CSIT error is dominated by channel estimation error. In this case, the proposed robust transceiver design seeks to minimize a stochastic function of the sum mean square error (SMSE) under a constraint on the total BS transmit power. We propose an iterative algorithm to solve this problem. The other model we consider is a norm-bounded error (NBE) model, where the CSIT error can be specified by an uncertainty set. This model is applicable when the CSIT error is dominated by quantization errors. In this case, we consider a worst-case design. For this model, we consider robust i) minimum SMSE, ii) MSE-constrained, and iii) MSE-balancing transceiver designs. We propose iterative algorithms to solve these problems, wherein each iteration involves a pair of semi-definite programs (SDP). Further, we consider an extension of the proposed algorithm to the case with per-antenna power constraints.

Multi-user multiple-input multiple-output (MU-MIMO) systems in the indoor visible light communication (VLC) have attracted significant attention due to the use of the lighting-emitting diodes (LEDs) for illumination and communication. However, they experience performance degradation due to interference from multiple users and low modulation bandwidth requiring the development of mitigation techniques. This work proposes a joint transceiver design using the minimum mean square error (MMSE) to minimize interference for the VLC systems. The mean square error (MSE) is minimised assuming perfect channel state information (CSI) to suppress the interference. The developed results show the proposed transceiver design providing fair data transmission and improving the bit error rate (BER) over the zero-forcing (ZF) scheme. Moreover, the proposed transceiver design shows better convergence than the ZF scheme.

Consider a MIMO multi-cellular network (also known as an interfering broadcast channel) where each base station transmits signals to the users in its own cell. The basic problem is to design linear transmit/receive beamformers and schedule users across a fixed set of time slots so as to maximize the system throughput in the presence of both inter and intra cell interference. In this paper, we propose a joint linear transceiver design and user grouping scheme for sum utility maximization that is based on iterative minimization of weighted mean squared error (MSE). The proposed algorithm only needs local channel knowledge and its convergence to a stationary point is guaranteed for some well-known utility functions, while ensuring user fairness. The simulation results show that the proposed formulation/algorithm can offer significantly higher system throughput than the standard multi-user MIMO techniques such as the SVD-MMSE strategy, while maintaining user fairness. Furthermore, the proposed algorithm exhibits fast convergence and is amenable to distributed implementation with limited information exchange.

This paper proposes a robust transceiver design against the effect of channel state information (CSI) estimation error to optimize precoded uplink (UL) multi-user multiple-input multiple-output (MU-MIMO) transmission in limited feedback system under the consideration of the least-square technique on CSI estimation. To improve this limited feedback precoding, the constrained minimum variance (MV) approach with quadratic form to realize the computationally-efficient optimization problem, advantageously invoking the characteristics of the CSI estimation error, is proposed to suppress the effect of CSI estimation error, multiple user interference and noise. According to the Lagrange multiplier method on this MV approach, the deterministic function to resist uncertain CSI can be obtained to optimize design of the precoder and adaptive matrices jointly. With these optimum adaptive and precoder matrices, an optimum robust weighting matrix can be obtained to facilitate the user-wise detection in precoded UL MU-MIMO system. Performance analysis shows that the proposed robust weighting matrix is an unbiased design and it also can regularize the diagonal loading factor technique, and the detection performance of the proposed robust transceiver design can be predicted simplistically by applying our derived signal-to-interference-plus-noise ratio formulation. Computer simulations are conducted to confirm the efficacy of the proposed design in both perfect and imperfect CSI estimation.

Multi-user multiple input multiple output (MU-MIMO) system is an excellent choice for the next generation broadband communications because of its great potential in enhancing MIMO system capacity. One major challenge of such system is the jointly optimal transceiver beamforming design that maximizes the sum capacity under a total power constraint. Existing approaches have provided convex optimization solution by exploiting the duality between transmitter and receiver. However, with high computation complexity, these approaches are ineligible of practical implementation. In this paper, we aim to provide complexity efficient transceiver beamformer and power allocation design in MU-MIMO downlink (broadcast) channels. We first develop an iterative sub-optimal algorithm based on cyclic self-SINR-maximization (CSSM) beamforming design and water-filling power allocation. Comparing to convex-optimization-based (COB) approaches, the proposed solution (i.e. CSSM-WF algorithm) have insignificant sum-rate degradation but very low computational complexity and extremely fast converging speed. Trying to improve the performance of CSSM-WF algorithm, we then introduce another algorithm denoted as efficient COB (ECOB) algorithm in which CSSM-WF algorithm is used to generate a good start point for optimal COB approaches. Simulation results prove the efficiency of both proposed algorithms.

In this paper, we investigate the robust transceiver design for a downlink multiuser multiple-input multiple-output (MIMO) amplify-and-forward (AF) relay system with imperfect channel state information (CSI). We consider that the actual channel is within the neighborhood of a nominal channel and formulate two optimization problems following the philosophy of worst-case robustness, i.e., minimizing the sum mean-square-error (SMSE) and minimizing the total transmit power for any channel realization in the uncertainty region. In order to efficiently find the solutions, we transform the original problems into suitable forms using the sign-definiteness lemma and then propose an alternating iterative algorithm with guaranteed convergence. To further reduce the computational complexity, the cutting-set method is developed, which alternates between transceiver design and channel determination steps. Moreover, some interesting extensions of the proposed methods are discussed, including various types of uncertainty models and transmit power constraints, nonlinear transceiver structure, and uncertain noise covariance. Simulation results are presented to demonstrate the effectiveness of the proposed robust designs.

Joint precoder and decoder optimization is considered for uplink multiuser multiple-input multiple-output (MU-MIMO) systems with limited channel state information (CSI) at both the transmitters and receivers. Instead of counting on complex iterative-based algorithms, an efficient and noniterative QR-based linear transceiver pair design is employed. In addition, an equal power distribution (EPD) scheme is applied to adjust transmit power allocation of each mobile station (MS) between its symbols under the total transmit-power constraint. Simulations are conducted to provide a comparative evaluation of the proposed QR-EPD algorithm with other transceiver designs on the sum mean-squared error (SMSE) and the averaged bit-error-rate (BER) performance.

<p>This thesis considers the analysis of current and future cellular communication systems. The main focus is on multiuser multiple-input multiple-output (MU-MIMO) antenna systems. The goal of this work is to characterize the achievable spectral efficiency of MU-MIMO systems, as well as to analyze the performance of practical, linear MU-MIMO transceiver structures in heterogeneous propagation environments. The analytical derivations in this thesis are based on the mathematical theory of finite and large dimensional random matrices. A collection of new general random matrix theory results, which permit efficient numerical evaluation are derived. With downlink regularized zero-forcing (RZF) processing at a cellular base station (BS), a general framework for the analysis of the expected (average) signal-to-interference-plus-noise-ratio (SINR) and ergodic sum spectral efficiency is developed for uncorrelated and semi-correlated Rayleigh fading, as well as uncorrelated Ricean fading propagation channels. In contrast to existing results, the presented analyses are extremely general, applicable to single-cellular, multi-cellular, as well as distributed antenna systems. These systems could consist of arbitrary numbers of transmit and receive antennas, link signal-to-noise-ratios (SNRs), equal and unequal transmit correlation structures, and line-of-sight (LoS) levels, respectively. Numerical results are presented for single-cellular, as well as for two-tier multi-cellular systems demonstrating the impact of novel BS coordination strategies to suppress dominant inter-cellular interference. With dominant LoS directions in the propagation channel, the instantaneous downlink zero-forcing (ZF) SNR of a given terminal is analyzed. The ZF SNR is shown to be approximated by a gamma distribution for any number of transmit and receive antennas, link SNRs, and LoS levels. Furthermore, for moderately sized MU-MIMO systems, simplified instantaneous and ergodic sum spectral efficiency analyses are presented with RZF, ZF and matched-filter (MF) transmission on the downlink, and minimum-mean-squared-error, ZF and maximum-ratio combining (MRC) on the uplink, respectively. The simple nature of the derived expressions lead to the discovery of several valuable system level insights as a function of the contributing network parameters. Numerical results are presented for conventional and moderate MU-MIMO systems. Considering downlink semi-correlated Rayleigh fading channels with spatial correlation at the BS, it is mathematically proven that common correlation patterns for each terminal predicts lower ergodic sum spectral efficiencies in comparison to terminal specific correlation patterns. Closed-form approximations for the expected SINR and ergodic sum spectral efficiency are derived for both MF and ZF precoding, demonstrating the sensitivity of unequal correlation structures on the expected signal, interference and noise powers, respectively. The presented numerical results provide a cautionary tale of the impact of unequal correlation patterns on MU-MIMO performance and the importance of modeling this phenomenon. Finally, an approximate uplink performance analysis of large MU-MIMO systems with MRC and space-constrained uniform linear antenna arrays (ULA) is presented for semi-correlated Ricean fading channels. A space-constrained channel model is proposed, encapsulating the effects of unequal receive spatial correlation, unequal LoS levels, and unequal link gains for each terminal. The per-terminal and cell-wide ergodic sum spectral efficiencies are characterized and numerous practical special cases are presented. A limiting analysis of the ergodic per-terminal and cell-wide spectral efficiencies is also carried out, as the number of BS antennas grow without bound with a finite number of terminals and fixed physical dimensions of the ULA. Numerical results demonstrate the impact of space-constrained ULAs on the MU-MIMO system performance with variation in the LoS levels, correlation structures, physical array dimensions, and system size, respectively.</p>

In this paper, we investigate linear precoding and scheduling algorithms for downlink multi-user multiple input multiple output (MU-MIMO) systems. In order to eliminate the multi-user interference and improve the bit error rate (BER) system performance, block diagonalization precoding could be combined with geometric mean decomposition (BD-GMD) scheme. We propose GMD linear precoding approaches utilizing oblique projection (OP-GMD). This paper also derives system capacity in closed-form through applying water-filling power allocation algorithm into the system model. Our simulation results show that the proposed scheduling algorithms perform better with the increase of the number of transmit antennas. In terms of system capacity, the proposed OP-GMD algorithms significantly outperform the precoding scheme based on BD-GMD at low SNRs.

Multi‐User Coordinated Multi‐Point (MU‐CoMP), which couples CoMP with Multi User‐Multiple Input Multiple Output (MU‐MIMO), appears as a promising solution to enhance the Long Term Evolution‐Advanced (LTE‐A) system performance. However, some challenging issues in MU‐CoMP networks require more investigation. First, the set of users transmitting under CoMP mode should be properly identified. Secondly, time‐frequency resource should be efficiently partitioned between CoMP and non‐CoMP users in order to improve the system radio capacity. Thirdly, a fair and green scheduler is much needed for a more energy efficient system. This paper deals with these three issues. We propose an adaptive transmission mode selection according to the total load in the cluster and to users' quality of service. The adequate size of the Spatial Division Multiple Access users' groups is also analyzed. We finally propose a new scheduling algorithm to further enhance the radio capacity and the energy consumption in the cluster. Simulations results showed that significant improvements are obtained in terms of total system throughput and outage probability in the cluster with our proposed scheme. Moreover, energy efficiency has increased by four times with our proposed scheduling algorithm as compared to commonly used schedulers. Copyright © 2015 John Wiley & Sons, Ltd.

An adaptive rate optimization solution is presented to utilize the benefits of multiuser multiple-input multiple-output (MU-MIMO) communications in a wireless network with distributed and decentralized control that adapts to dynamic channel, interference, and traffic conditions. First, the ergodic sum rates of MIMO multiple access channel (MAC) and interference channel (IC) configurations are determined by jointly integrating the error and overhead effects due to channel estimation (training) and feedback into the rate optimization. Then, a distributed channel access protocol that leverages local information without any centralized scheduler is developed to select and activate MU-MIMO configurations with the maximum achievable sum rates depending on channel, interference, and traffic conditions. In a mobile ad hoc network (MANET), MU-MIMO is shown to provide major gains in network throughput (after accounting for the control message overhead) compared with single antenna and point-to-point (P2P) MIMO communications.

Efficient channel feedback methods are becoming more important in limited-feedback multi-user multiple input multiple output (MU-MIMO) systems. We propose a new dynamic channel feedback control (DEFCON) scheme, which efficiently allocates the limited system resources for channel feedback to appropriate users. The main features of the proposed DEFCON scheme are as follows. Firstly, the channel feedback procedure is composed of two stages: rough channel feedback of all users and additional precise channel feedback of the selected users only. Secondly, each selected user is allocated with different amount of resources for additional channel feedback according to its channel status. We mathematically solve the resource allocation problem by proposing a suboptimal method, which utilizes convex optimization technique combined with iterative steepest decent direction search algorithm. Numerical results show that zero-forcing beamforming (ZFBF) with the proposed DEFCON scheme considerably outperforms previous limited-feedback MU-MIMO schemes such as ZFBF with conventional static feedback method and per user unitary beamforming rate control (PU <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> RC).

Consider the multiple-input multiple-output (MIMO) interfering broadcast channel whereby multiple base stations in a cellular network simultaneously transmit signals to a group of users in their own cells while causing interference to each other. The basic problem is to design linear beamformers that can maximize the system throughput. In this paper, we propose a linear transceiver design algorithm for weighted sum-rate maximization that is based on iterative minimization of weighted mean-square error (MSE). The proposed algorithm only needs local channel knowledge and converges to a stationary point of the weighted sum-rate maximization problem. Furthermore, the algorithm and its convergence can be extended to a general class of sum-utility maximization problem. The effectiveness of the proposed algorithm is validated by numerical experiments.

In this paper, we introduce a joint antenna selection and user sorting scheme in multi-user multiple-input multiple-output (MU-MIMO) systems, in which Tomlinson-Harashima precoding (THP) is adopted. In MU-MIMO with THP, antenna selection and user sorting are important means to improve the system performance. By considering the interrelationship between antenna selection and user sorting in THP, based on the scheme, we propose an efficient algorithm to solve the antenna selection and user sorting jointly, which achieves near performance of the optimal one obtained by exhaustive search. Analytical results demonstrate the proposed scheme has low complexity. Simulation results show the availability of our proposed scheme.