Chun-Tao Lin

QRD-Based Antenna Selection for ML Detection of Spatial Multiplexing MIMO Systems: Algorithms and Applications

Antenna selection is a simple but effective technique to enhance the performance of a spatial multiplexing multiple-input-multiple-output (MIMO) system. The selection criterion depends on the detector used at the receiver. For the maximum-likelihood detector, the criterion is to maximize the free distance. However, an exhaustive search is required to derive the distance, and the computational complexity can be prohibitively high. To avoid the exhaustive search, a lower bound of the free distance derived with the singular value decomposition (SVD) was then developed. This bound only involves the smallest singular value of the channel matrix, and its maximization can easily be conducted. An alternative lower bound of the free distance with the QR decomposition (QRD) was also derived in the literature. In this paper, we first propose a QRD-based selection method maximizing the lower bound. With some matrix properties, we theoretically prove that the lower bound yielded by the QRD is tighter than that by the SVD. We then propose a basis transformation method so that the lower bound yielded by the QRD can further be tightened. As a result, the QRD-based selection method can achieve near optimum performance. Finally, we extend the use of the proposed methods to other applications, such as receive antenna selection, joint transmit/receive antenna selection, and antenna selection in MIMO relay systems. Simulations show that the proposed selection methods can significantly outperform existing methods.

Low-Complexity ML Detectors for Generalized Spatial Modulation Systems

Spatial modulation (SM) combined with spatial multiplexing is a newly developed transmission scheme in multiple-input multiple-output (MIMO) systems. The resultant system, referred to as generalized SM (GSM), can use the maximum-likelihood (ML) detector jointly detecting the antenna-subset (AS) index and symbol vector. As known, the ML detector can achieve optimum performance; however, its computational complexity can be prohibitively high when the dimension of the GSM system is large. In this paper, we propose new methods to solve the problem. The main idea is to split the detection into two stages, one for the AS index and the other for the symbol vector. For the detection of the AS index, we develop two methods, referred to as Gaussian approximation and QR projection. Once the AS index is detected, conventional low-complexity ML detectors can be applied for the detection of the symbol vector. The diversity order for the proposed methods are further analyzed and an enhanced method is also proposed to achieve near-optimum performance. Finally, the proposed methods are extended to conduct soft detection of GSM systems. Simulations show that our methods significantly outperform existing ones while the detection complexity remains similar.

QRD-based antenna selection for maximum-likelihood MIMO detection

Antenna selection is a simple but effective method to exploit the transmit diversity in multiple-input multiple-output (MIMO) wireless communications. For maximum-likelihood (ML) detectors, the criterion for the selection is to maximize the free distance of the MIMO system. Since the optimum selection is difficult to conduct, a lower bound of the free distance is typically used as the selection criterion instead. The singular-value-decomposition (SVD) based selection criterion is well known in the literature. In this paper, we propose a QR decomposition (QRD) based selection criterion for antenna selection with the ML detector. Using some matrix properties, we theoretically prove that the lower bound achieved with the QRD-based criterion is tighter than that with the SVD-based criterion. We also propose another QRD-based criterion that can further tighten the lower bound. The proposed algorithms can be directly applied to the receive, and joint transmit/receive antenna selection schemes. Simulations show that the performance of the proposed selection criteria can significantly outperform the SVD-based selection criterion.

Optimum Transceiver Designs in Two-Hop Amplify-and-Forward MIMO Relay Systems With SIC Receivers

We consider joint source/relay precoding in three-node two-hop amplify-and-forward (AF) multiple-input-multiple-output (MIMO) relay systems. In our systems, linear precoders are used at the source and the relay, and the QR successive interference cancelation (SIC) receiver is used at the destination. Our design criterion is to minimize the block error rate (BLER) of the receiver. Since the BLER is a complicated function of the source and relay precoders, and the power constraints are coupled, the optimization problem is difficult to solve. To overcome the difficulty, we first apply the primal decomposition approach, transforming the original optimization to a subproblem and a master problem. In the subproblem, the optimum source precoder can be obtained with the geometric mean decomposition (GMD). In the master problem, however, the optimum relay precoder cannot be straightforwardly obtained. We theoretically prove that the optimum relay precoder exhibits a matrix diagonalization property. Using this property, we can then transform the master problem into a scalar-variable concave optimization problem. A closed-form solution can be derived by the Karuch-Kuhn-Tucker (KKT) conditions. Finally, we extend our method to the two-hop AF MIMO relay system with the minimum mean square error (MMSE) SIC receiver. Assuming a unitary source precoder, we obtain the optimum source and relay precoders in closed form. Simulations show that the proposed transceivers can significantly improve the system performance.

Clipping ratio estimation for OFDM receivers

Signal clipping is known to be the simplest method to reduce the peak to average power ratio (PAPR) in OFDM systems. Clipping introduces the clipping noise (CN) degrading system performance. Most clipping noise mitigation algorithms require to know the clipping ratio (CR) in the receiver, however, this may not be possible for all applications. We propose a new clipping ratio estimation method which can be applied to pilot-tone-based OFDM systems. Simulation results show that the proposed algorithm can estimate CR accurately and clipping noise can be effectively mitigated.

X-structured precoder design for spatial multiplexing MIMO systems

In multiple-input multiple-output (MIMO) transmission, precoding has been considered a promising method to improve the system performance. In general, the precoder design criterion depends on the detector used at the receiver. For the maximum-likelihood (ML) detector, the optimum precoder design criterion is equivalent to maximizing the minimum distance of received signal constellations. Several precoding methods have been developed in the literature. However, most of them use numerical searches to derive the precoders and require table look-ups in realtime applications. In this paper, we propose a simple but effective method to solve the problem. The proposed precoder has a simple closed-form expression and no tables are required to store. Simulation results show that the proposed precoder can provide almost the same performance as existing precoders.

MMSE Transceiver Design for Full-Duplex MIMO Relay Systems

Full-duplex (FD) multiple-input multiple-output relaying has been considered an effective scheme to increase the spectral efficiency for wireless communications. As known, the main problem for the FD system is the cancellation of loop interference (LI). In this paper, we propose using the joint source/relay precoding to reduce the influence of LI. Therein, linear precoders are used at the source and relay, while the minimum mean-squared-error receiver is adopted at the destination. The joint precoder design is complicated when spatial multiplexing is exploited for signal transmission. To solve the problem, we propose an iterative method in which the original problem is split into two subproblems. With some matrix properties, we then show that each subproblem can be formulated as a convex optimization. Finally, a closed-form solution can be obtained with the Karush–Kuhn–Tucker conditions. Using a mean-squared-error upper bound, we also propose a low-complexity method to reduce the computational complexity. The proposed precoders have closed-form expressions, which is a great advantage in real-world implementation. Simulation results show that the proposed methods significantly outperform existing ones.

X-Structured Precoder Designs for Spatial-Multiplexing MIMO and MIMO Relay Systems

In multiple-input-multiple-output (MIMO) transmission, precoding has been considered a promising technique to improve the system performance. In general, the criterion of precoder design depends on the detector used at the receiver. For the maximum-likelihood (ML) detector, the criterion is to maximize the minimum distance of the received signal constellation. Unfortunately, the derivation of the optimum solution is known to be difficult, and suboptimum solutions have then been developed. One promising approach confines the precoder having an X-structure. Several methods have been developed to solve the X-structured precoder. However, most of them use numerical searches to find their solutions and require lookup tables during run time. In this paper, we propose a systematic design method to solve the problems. The proposed precoder has a simple closed-form expression, and no numerical searches and lookup tables are required. Simulation results show that the proposed method can yield almost the same performance as the existing methods. We also consider the problem of joint source/relay precoder design in a two-hop amplify-and-forward MIMO relay system. Since the problem is much more involved and a closed-form solution is intractable to find, we then extend the use of the proposed X-structured precoder so that the problem can be reformulated as a simple scalar-valued optimization problem. Simulations show that the proposed method can significantly outperform existing joint design methods.

Linear Transceiver Design for Full-Duplex MIMO Relay Systems: A Non-Iterative Approach

Full-duplex (FD) multiple-input multiple-output relaying can significantly increase the spectral efficiency of cooperative systems. As known, the loop interference (LI) is a main factor affecting the performance of FD systems. The joint source/relay precoding has been considered a promising technique to reduce the influence of LI. Unfortunately, existing methods are developed as iterative, which is not desirable from the implementation point of view. In this letter, we propose a novel design to solve the problem. The proposed scheme not only gives closed-form solutions but avoids iterative operations. Simulation results show that our design can provide comparable performance to iterative schemes; meanwhile the required computational complexity is lower.

X-structured precoder design for multiuser MIMO communications

One problem in multiuser multiple-input multiple-output (MU-MIMO) systems is that the transmitted signal from a base station to a user is interfered by the signals to other users. MU-MIMO precoding has been proposed as an effective way to solve the problem. However, most existing precoding methods are mainly designed with zero-forcing (ZF) or minimum mean-square-error (MMSE) criterion and the performance is not optimal. In this paper, we consider a precoding scheme for MU-MIMO systems where maximum-likelihood (ML) detection is used for each user. We propose using a newly developed X-structured precoder which is specifically optimized for the ML detection. In our method, multiuser interference is first mitigated by using a regularized block diagonalization (RBD) technique. Then, an iterative method is used to construct the X-structured precoder so that the performance of the ML detection can be enhanced. Numerical results show that the proposed method can significantly outperform existing precoding methods.