Search

This paper studies the impact of channel error on the achievable rate of symmetrical K-user multiple-input multiple-output linear interference alignment (IA) networks. The upper and lower bounds of the achievable sum rate are derived analytically with the assumption of orthonormal transmit precoders and receive filters designed from imperfect channel state information (CSI) over both the uncorrelated and correlated channels. For uncorrelated channels, quite tight lower and upper bounds are obtained. The impact of channel error on the degrees of freedom (DoF) and the DoF persistence conditions are also investigated. Results show that the DoF of IA networks persists only if the channel error decreases in an order higher than the signal-to-noise ratio. For correlated channel, the lower and upper bounds for one realization of IA are derived. The derived upper bound can be used to characterize the achievable rate approximately. Simulation results indicate that the achievable rate of IA network is influenced significantly by CSI uncertainty. The obtained analytical bounds provide an intuitive way to show the impact of channel error on the achievable rate and thus can help practical systems deign. [ABSTRACT FROM AUTHOR]

This paper investigates the energy efficient downlink transmission in distributed massive multiple-input–multiple-output systems, where massive antennas are clustered on geographically distributed remote radio heads (RRH). A closed form of the ergodic achievable rate is derived for a specific RRH-user association and imperfect channel state information to assist the formulation of its system energy efficiency (EE). By assuming minimum user achievable rate requirements and a practical power consumption model including both the transmit power and the antenna circuit power, an optimization problem is formulated to maximize the system EE with respect to the power allocation, the antennas activation, and the RRH-user association in a combinatorial manner. The formulated problem is a mixed-integer nonlinear programming problem, which is NP-hard and usually has no feasible solution. To solve it, an efficient algorithm is proposed by utilizing hierarchical decomposition technique and iterative successive convex approximation. The feasibility as well as the effectiveness of the proposed algorithm are analyzed and proved through analysis and intensive computer simulations. Results show that the system EE can be greatly improved by the proposed scheme. [ABSTRACT FROM AUTHOR]

The bits-to-antenna-index (BAI) and bits-to-modulated-symbol (BMS) mappings play important roles in determining the bit error rate (BER) of spatial modulation (SM). To minimize the BER, a plenty of work has paid much attention on optimizing the noise-free receive signal constellation diagram via adaptive power allocation, phase ration, precoding, etc, but overlooked the impact of the BAI and BMS mappings. To fill in this gap, this paper investigates the adaptive mapper design for SM, and proposes a mapper solution named brute forth mapper (BFM). Through adjusting the binary labels of all the closest symbol-pairs to be of one bit difference in a brute force way, BFM achieves the optimal BER in high signal-to-noise-ratio (SNR) regime. The feasibility of BFM is proved over random fading channels, and the performance improvement brought by BFM in terms of BER enhancement and SNR gain as well as the computational complexity and feedback overhead are quantitatively analyzed. Both analysis and simulations show that the proposed adaptive mapper significantly improves the BER performance with lightweight feedback overhead. [ABSTRACT FROM PUBLISHER]

This paper studies the joint transceiver design and power splitting (JTDPS) for a downlink multiuser multiple-input multiple-output (MU-MIMO) simultaneous wireless information and power transfer (SWIPT) system. Aiming to minimize the transmit power by jointly optimizing the transmitter at a base station, the power splitting (PS) factors, and information decoding receivers at mobile stations (MSs) subject to both the predefined mean-square error (MSE) and the given energy harvesting (EH) constraints. The formulated problem is a nonconvex JTDPS optimization problem, which cannot be solved directly. To solve it, an iterative optimization framework composed of joint transmitter and PS factor optimization (JTxPS) subproblem and a receiver side minimum mean-square error (MMSE) minimization subproblem is proposed. By iteratively solve the two subproblems, the original optimization problem is solved. The sufficient and necessary conditions for the feasibility of the formulated JTDPS and the JTxPS problems are analyzed. Theoretical analysis shows that the JTxPS subproblem is also nonconvex and can be solved by using convex semidefinite programming (SDP). Considering the high computational complexity of the SDP-based scheme, a low-complexity suboptimal scheme based on the traditional MMSE transceiver design is also proposed. Simulations are done to validate the theoretical analysis, and results show the effectiveness of the proposed schemes. [ABSTRACT FROM AUTHOR]

Spatial modulation (SM) conveys information bits by utilizing both the antenna index and complex symbols to form a 3-D constellation. Similar to 2-D modulation, the structure of 3-D constellation could greatly affect the transmission reliability. In this paper, a generalized 3-D constellation design is proposed to optimize the constellation diagram used for each antenna, i.e., to optimize the complex symbols and their total number for each antenna and finally to enhance the transmission reliability. The optimal design method with exhaustive search algorithm may cause prohibitive computational complexity, especially when the cardinality of 3-D constellation is large. To overcome this issue, a recursive design algorithm is proposed with a computational complexity increasing polynomially with the cardinality of 3-D constellation. Extensions of the proposed methods to the SM constellation design for massive multiple-input multiple-output transmission, generalized spatial modulation (GSM) constellation design, and the SM constellation design with transmit antenna correlation are also discussed. Simulations are done to validate those theoretical analysis, and results show that the proposed 3-D constellation design is a generalized design scheme and can be adopted in any SM/GSM systems without constraints on the number of transceiver antennas. It is also shown that the proposed approach offers better symbol-error-rate performance than other solutions. [ABSTRACT FROM PUBLISHER]

This work focuses on the design and analysis of link-adaptive bits-to-antenna-indexes mapping for closed-loop space-shift keying (SSK)-modulated multiple-input multiple-output (MIMO) systems. With the aim of achieving a lower bit error rate (BER), optimal mappers are designed under different transmission conditions. Assuming that perfect channel state information (CSI) is available at the transceivers, an original binary switch algorithm (OBSA) is proposed. For the case in which there is no CSI at the transmitter and the feedback channel is bandwidth limited, a restricted binary switch algorithm (RBSA)-based mapping design is proposed. Both of the proposed algorithms can bring considerable performance gains but are of high computational complexity if there are a large number of transmit antennas. To overcome this, algorithms with reduced computational complexity are proposed and investigated, which are named partial OBSA and partial RBSA. The performance improvement brought by all of the proposed mapping schemes in terms of BER performance enhancement and signal-to-noise ratio (SNR) gain in a high-SNR regime is theoretically given. Simulations are done to validate the theoretical analysis, and results show that the proposed schemes can improve BER performance considerably in a wide range of SNR regimes. In addition, all of the proposed mapping schemes can cowork with those existing transmit processing techniques and bring additional performance gain without incurring any extra cost on physical components (e.g., additional phase shifters or power amplifiers). All these make the proposed mapping schemes promising choices for the link-adaptive design of closed-loop SSK MIMO systems. [ABSTRACT FROM PUBLISHER]

An interference alignment (IA) transceiver design scheme for multiple-input–multiple-output (MIMO) multicell multiuser wireless communication systems is proposed by minimizing the maximum mean square error (MSE) of the received symbols to improve fairness among users. The formulated Min-Max MSE optimization problem is not jointly convex on the transmit precoders and receive filters and, thus, is very difficult to solve directly. An iterative method is proposed to solve the optimization problem to get a suboptimal solution instead. Considering that if the receive filters are fixed, the Min-Max MSE problem can be reformulated as a second-order cone programming problem, and if the transmit precoders are fixed, the closed-form receive filters minimizing the receive MSE can be easily obtained, and the formulated Min-Max MSE problem is solved by alternatively optimizing the transmit precoders and the receive filters. The convergence of the proposed algorithm is proved, which shows its feasibility. Furthermore, a robust Min-Max MSE algorithm is proposed to counter the channel uncertainty. Simulation results show that the proposed Min-Max MSE algorithm can achieve IA when the antennas are configured to be strong IA proper and when the users in the network are of the same signal-to-noise ratio (SNR). Analysis indicates that the proposed Min-Max IA transceiver design scheme can significantly improve user fairness with a possible cost of sum-rate reduction. Results also show that the proposed robust design algorithm provides better performance when lacking perfect channel state information (CSI). [ABSTRACT FROM AUTHOR]

This paper proposes a power allocation scheme to maximize the sum capacity of all users for signal-to-leakage-and-noise ratio (SLNR) precoded multiuser multiple-input single-output downlink. The designed scheme tries to explore the effect of the power allocation for the SLNR precoded multiuser multiple-input single-output system on sum capacity performance. This power allocation problem can be formulated as an optimization problem. With high signal-to-interference-plus-noise ratio assumption, it can be converted into a convex optimization problem through the geometric programming and hence can be solved efficiently. Because the assumption of high signal-to-interference-plus-noise ratio cannot be always satisfied in practice, we design a globally optimal solution algorithm based on a combination of branch and bound framework and convex relaxation techniques. Theoretically, the proposed scheme can provide optimal power allocation in sum capacity maximization. Then, we further propose a judgement-decision algorithm to achieve a trade-off between the optimality and computational complexity. The simulation results also show that, with the proposed scheme, the sum capacity of all the users can be improved compared with three existing power allocation schemes. Meanwhile, some meaningful conclusions about the effect of the further power allocation based on the SLNR precoding have been also acquired. The performance improvement of the maximum sum capacity power allocation scheme relates to the transmit antenna number and embodies different variation trends in allusion to the different equipped transmit antenna number as the signal-to-noise ratio (SNR) changes.Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY This paper proposes a joint precoding and power allocation strategy to maximize the sum rate of multiuser multiple-input multiple-output (MIMO) relay networks. A two-hop relay link working on amplify-and-forward (AF) mode is considered. Precoding and power allocation are designed jointly at the base station (BS). It is assumed that there are no direct links between the BS and users. Under individual power constraints at the BS and relay station, precoders designed based on zero forcing, minimum mean-square error and maximum ratio transmission are derived, respectively. Optimal power allocation strategies for these precoders are given separately. To demonstrate the performance of the proposed strategies, we simulate the uncoded bit error rate performance of the underlined system. We also show the difference of the sum rate of the system with the optimal power allocation strategies and with average power transmission. The simulation results show the advantages of the proposed joint precoding and power allocation strategies as expected. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, we propose a quasi-orthogonal space-time block coding (QO-STBC) orthogonal frequency-division multiplex (OFDM) scheme for its application in frequency-selective channels. A novel decoding approach for QO-STBC OFDM is introduced, and it works based on an array-processing technique. The received QO-STBC OFDM symbol array is decomposed by null spaces of the split-up channel matrices, followed by a parallel decoding unit, as an effort to reduce the computational complexity and latency induced by the decoding process. The performance of the proposed system is evaluated over frequency-selective channels by both analysis and computer simulations to show the effectiveness of the scheme. [ABSTRACT FROM AUTHOR]

In this paper, we propose a linear assignment problem (LAP) scheme using greedy algorithms to alleviate the intercell interference (ICI) in massive multi-input multiple-output (maMIMO) systems. ICI has been recognized as one of the main challenges of massive MIMO systems and occurs when pilot sequences (PSs) are reused across neighboring cells or using non-orthogonal PS, and this results in a phenomenon known as pilot contamination (PC). The proposed scheme uniquely assigns pilot sequences to mobile terminals to mitigate PC such that the optimal or near-optimal solution is achieved. This scheme attains maximum SINR by assigning pilot sequence to mobile terminals that will only produce the least PC. Results obtained from simulation showed that the proposed assignment scheme achieved a greater sum rate than some established assignment schemes when compared. [ABSTRACT FROM AUTHOR]