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This paper considers joint linear processing at multi-antenna sources and one multiple-input multiple-output (MIMO) relay station for both one-way and two-way relay-assisted wireless communications. The one-way relaying is applicable in the scenario of downlink transmission by a multi-antenna base station to multiple single-antenna users with the help of one MIMO relay. In such a scenario, the objective of join linear processing is to maximize the information throughput to users. The design problem is equivalently formulated as the maximization of the worst signal-to-interference-plus-noise ratio (SINR) among all users subject to various transmission power constraints. Such a program of nonconvex objective minimization under nonconvex constraints is transformed to a canonical d.c. (difference of convex functions/sets) program of d.c. function optimization under convex constraints through nonconvex duality with zero duality gap. An efficient iterative algorithm is then applied to solve this canonical d.c program. For the scenario of using one MIMO relay to assist two sources exchanging their information in two-way relying manner, the joint linear processing aims at either minimizing the maximum mean square error (MSE) or maximizing the total information throughput of the two sources. By applying tractable optimization for the linear minimum MSE estimator and d.c. programming, an iterative algorithm is developed to solve these two optimization problems. Extensive simulation results demonstrate that the proposed methods substantially outperform previously-known joint optimization methods. [ABSTRACT FROM PUBLISHER]

In this paper, we start by investigating the impact of joint transmit-receive I/Q imbalance on the performance of direct-conversion beamforming OFDM transceivers. We derive a new analytical expression for the average subcarrier SINR of the I/Q imbalance-ignorant beamformer in terms of the I/Q imbalance level at both the transmit and receive sides, the size of the beamforming array, and the input SNR level. This expression motivates the need for I/Q imbalance compensation and provides valuable design insights when examining several special and limiting cases. Next, we derive the throughput-maximizing multiple beamforming transmit/receive coefficients under a general system model with an asymmetric frequency-dependent (FD) joint transmit-receive I/Q imbalance. In addition, we propose a low-complexity pilot-aided scheme for the estimation of the channel and I/Q imbalance parameters. Our simulation results demonstrate that the proposed generalized multiple beamforming scheme is highly effective in mitigating I/Q imbalance effects at practical complexity levels. [ABSTRACT FROM AUTHOR]

Interference alignment (IA) is known to significantly increase sum-throughput at high SNR in the presence of multiple interfering nodes, however, the reliability of IA is little known, which is the subject of this paper. We study the error performance of IA and compare it with conventional orthogonal transmission schemes. Since most IA algorithms require extensive channel state information (CSI), we also investigate the impact of CSI imperfection (uncertainty) on the error performance. Our results show that under identical rates, IA attains a better error performance than the orthogonal scheme for practical signal to noise ratio (SNR) values but is more sensitive to CSI uncertainty. We design bit loading algorithms that significantly improve error performance of the existing IA schemes. Furthermore, we propose an adaptive transmission scheme that not only considerably reduces error probability, but also produces robustness to CSI uncertainty. [ABSTRACT FROM PUBLISHER]

Recent works on multiuser MIMO study have shown that the linear growth of capacity in single user MIMO system can be translated to the multiuser MIMO scenario as well. In this paper, we propose a method pursuing performance gain of vector perturbation in multiuser downlink systems. Instead of employing the maximum number of mobile users for communication, we use small part of them as virtual users for improving reliability of users participating communication. By controlling parameters of the virtual users including information and perturbation vector, we obtain considerable improvement in the effective SNR. Simulation results on the realistic multiuser MISO and MIMO downlink systems show that the proposed method brings substantial performance gain over the standard vector perturbation with marginal overhead in computations. [ABSTRACT FROM AUTHOR]

In this paper, we propose a linear precoder for the downlink of a multi-user MIMO system with multiple users that potentially act as eavesdroppers. The proposed precoder is based on regularized channel inversion (RCI) with a regularization parameter α and power allocation vector chosen in such a way that the achievable secrecy sum-rate is maximized. We consider the worst-case scenario for the multi-user MIMO system, where the transmitter assumes users cooperate to eavesdrop on other users. We derive the achievable secrecy sum-rate and obtain the closed-form expression for the optimal regularization parameter αLS of the precoder using large-system analysis. We show that the RCI precoder with αLS outperforms several other linear precoding schemes, and it achieves a secrecy sum-rate that has same scaling factor as the sum-rate achieved by the optimum RCI precoder without secrecy requirements. We propose a power allocation algorithm to maximize the secrecy sum-rate for fixed α. We then extend our algorithm to maximize the secrecy sum-rate by jointly optimizing α and the power allocation vector. The jointly optimized precoder outperforms RCI with αLS and equal power allocation by up to 20 percent at practical values of the signal-to-noise ratio and for 4 users and 4 transmit antennas. [ABSTRACT FROM AUTHOR]

In a cellular-like system, the multiple-input multiple-output (MIMO) mode used by a base station (BS) can be adaptively varied among several candidate MIMO modes, including space-time block coding (STBC), open-loop spatial multiplexing (OLSM), closed-loop spatial multiplexing (CLSM), MIMO beamforming (MBF), and maximal ratio transmission (MRT). In practice, during any one given period of time, when the desired BS performs downlink transmission with a specific MIMO mode, each co-channel interfering BS will use a MIMO mode the same as or different from that used in the desired link and any two co-channel interfering BSs may use different MIMO modes, so that the interference scenario becomes quite complicated. In this paper, considering realistic propagation conditions including both path-loss and Rayleigh fading and considering the existence of unequal-power interferers, the statistical distributions of the post-processing signal-to-interference ratios (SIRs) for either MBF or STBC downlink transmissions are analyzed when co-channel interfering BSs employ arbitrary MIMO modes. In particular, closed-form expressions for the probability density function (PDF) of the interference terms in the post-processing SIRs are derived. Further, the statistical distributions of the post-processing SIRs are analyzed. Simulation results verify the validity of the theoretical analyses. [ABSTRACT FROM PUBLISHER]

For multi-user interference channels (IC), an altruistic approach based on the zero-forcing (ZF) criterion shows the near-optimal performance at high signal-to-noise ratio (SNR), whereas its performance at low SNR becomes poor compared to a simple egoistic algorithm (selfish beamforming). Thus, balancing between the egoism and the altruism has been an important issue to achieve good sum-rate performance at overall SNR regime. In this paper, we propose a new approach for enhancing the performance by regularizing the ZF based transceivers. To this end, we start with investigating efficient ZF transceivers for 2-user and 3-user ICs. First, coordinated spatial multiplexing (CSM) is proposed for 2-user IC. For the 3-user case, it is shown that the enhanced interference alignment (E-IA) introduced in our previous work is the optimal ZF transceivers in terms of the sum-rate performance. Next, to improve the performance of the CSM and E-IA schemes at low SNR, we propose a non-iterative regularization method under the high SNR approximation. The distributed implementation of the proposed regularization method is also presented where each node is able to compute its own precoding or decoding matrix using local channel state information. From simulations, it is observed that the proposed regularized design outperforms the conventional schemes in overall SNR regime. Also, we confirm that our distributed approach provides a substantial performance gain over the conventional distributed scheme with reduced computational complexity. [ABSTRACT FROM PUBLISHER]

The signal to interference plus noise ratio (SINR) feedback has been utilized in random beamforming (RBF) to select users for multiple-input multiple-output (MIMO) systems where a large number of users are required to obtain a multi-user diversity gain. However, if the number of users is not large enough, it may be difficult to obtain the performance gain and be easy to have a performance degradation conversely. To resolve this problem, it is necessary to find orthogonal random beams close to the channel matrix of selected users. In this paper, we present RBF using a non-orthogonal beamforming matrix (RBF NOBM), demonstrating an efficient search of random beams correlated with the channel matrix of selected users over a small number of users. For single user RBF using NOBM (SU-RBF NOBM) with two transmit antennas, the beamforming matrix for user data service is obtained through closed form expressions, and SU-RBF NOBM is then expanded to more than two transmit antennas. We also propose user selection algorithms for SU-RBF NOBM and multi-user RBF using NOBM (MU-RBF NOBM). Via simulation results, we demonstrate that the performances of RBF NOBM represent significant improvements compared to conventional beamforming schemes. [ABSTRACT FROM PUBLISHER]

In this paper, we propose jointly-optimized beamforming algorithms for cognitive networks to maximize the achievable rates, where primary and cognitive users share the same spectrum and are equipped with multiple antennas. We consider the transmission of a single information stream in both primary and secondary links. No coordination is required between the primary and cognitive users and the interference cancellation is done at the cognitive user. Specifically, the beamforming vectors of the cognitive link are designed to maximize the achievable rate under the condition that the interference both at the primary and cognitive receivers is completely nullified. Furthermore, it is proved that the achievable rate of a general N_t^Cx 2 (N_t^C transmit antennas at the cognitive transmitter and 2 receive antennas at the cognitive receiver) cognitive multiple-input multiple-output (MIMO) link employing the optimal proposed beamformers (which completely nullifies the interference to and from the primary link while maximizing its own achievable rate) is the same as the rate of an interference-free (N_t^C-1)x 1 multiple-input single-output (MISO) link employing an optimal maximal ratio transmission beamforming vector. The sum rate performance of the proposed algorithms is evaluated by Monte Carlo simulations. The impact of the number of transmit and receive antennas on the proposed algorithm is also discussed. [ABSTRACT FROM AUTHOR]

In downlink multiuser multiple-input multiple-output (MIMO) systems, system performance highly depends on the reliability of downlink channel state information (CSI) at the base station (BS). In frequency division duplexing, the most practical solution is to have downlink CSI from the users fed back to the BS. Most work on this feedback design has assumed independent block fading channels. However, this paper proposes a new differential feedback scheme using the observation that the channel realizations are usually temporally correlated. The sum-rate loss assuming differential feedback is analyzed for a system with the number of users K equal to the number of transmit antennas M. When K > M, a user selection algorithm based on an approximated signal-to-interference plus noise ratio (SINR) estimation is proposed. In simulation results, the proposed differential feedback scheme increases the sum-rate compared to previous differential feedback schemes. Moreover, the proposed user selection algorithm outperforms semi-orthogonal user selection in the moderate signal-to-noise ratio (SNR) region, despite requiring less feedback information. In low mobility channels, utilizing the channels' time correlation during quantization is shown to play a bigger role in determining sum-rate performance than multiuser diversity for most SNR regimes when a practical number of users is considered. [ABSTRACT FROM AUTHOR]