Multiple-input Multiple-output Broadcast Systems Research Articles

Spherical-Cap Approximation of Vector Quantization for Quantization-Based Combining in MIMO Broadcast Channels with Limited Feedback

The spherical-cap approximation of vector quantization (SCVQ) is an analytical model used for the mathematical analysis of multiple-input multiple-output (MIMO) systems with limited feedback. SCVQ closely emulates the distribution of the quantization error induced by the finite-rate quantization of a channel using a simple and analytically tractable approach. However, the conventional SCVQ model is not applicable when antenna-combining schemes such as quantization-based combining (QBC) are considered. Because QBC is an effective antenna-combining method that minimizes channel quantization errors, it can be adopted for various practical MIMO broadcast systems. Nevertheless, evaluating the performance of QBC-based MIMO systems with an explicit codebook can be extremely difficult, depending on the system complexity. To resolve this, this study generalizes the conventional SCVQ to be compatible with the QBC. The proposed generalized version of the SCVQ effectively emulates the quantization error obtained using QBC, while enabling a simple simulation independent of the number of feedback bits and mathematically tractable analysis. We validate the effectiveness of the proposed model by presenting a wireless communication application based on a dense cellular network.

On the Accuracy of Quantization Cell Approximation in MIMO Broadcast Systems Based on Limited Feedback

This study investigates the accuracy of quantization cell approximation (QCA) in a multiple-input multiple-output (MIMO) broadcast channel. QCA is an analytical quantization model used to approximate the quantized channel state information (CSI) in limited-feedback-based MIMO systems. It has been widely used in important studies for analytical tractability because it approximates the quantized CSI as a simple beta random variable multiplied by a deterministic value. Moreover, the effect of quantization is solely concentrated on the deterministic value such that the corresponding performance analysis is stochastically independent of the quantization process. Nevertheless, the accuracy of QCA has not been carefully demonstrated in previous studies. In this study, a generalized version of QCA is proposed with a complete analysis. Because the proposed QCA requires the use of a specific distance measure, the validity of the distance measure is first investigated. Based on the proposed distance measure, the accuracy of QCA is estimated by analyzing the difference between the spectral efficiencies achieved using QCA and random matrix quantization (RMQ). The corresponding results show that the difference gradually decreases and converges to zero as the number of feedback bits increases. As QCA and RMQ provide performance upper and lower bounds, respectively, in terms of codebook construction, these results prove the asymptotic validity of QCA with respect to the number of feedback bits. Both analysis and simulation results demonstrate that the difference in spectral efficiencies is also small for a moderate number of feedback bits. In addition, this study also demonstrates an asymptotic difference in spectral efficiencies with respect to the signal-to-noise-ratio (SNR). The difference increases with the SNR, but it is bounded by a finite value. Thus, the difference in the worst case SNR can also be suppressed by increasing the number of feedback bits.

Antenna Selection for Simultaneous Wireless Information and Power Transfer in MIMO Systems

For simultaneous wireless information and power transfer in multiple-input multiple-output broadcast systems, we propose to investigate the antenna selection (AS) design problem. The problem is formulated as joint AS and transmit covariance matrix design optimization problem which maximizes the achievable rate from the transmitter to the information-decoding receiver subject to the energy-harvesting constraint and the transmit power constraint. To solve the problem, we relax the binary constraints on the AS matrices and restrict the transmit covariance matrix to be diagonal. The AS matrices and the transmit covariance matrix are optimized iteratively by our proposed iterative AS algorithm. We also propose a low-complexity non-iterative norm-based algorithm which optimizes the AS matrices and the transmit covariance matrix sequentially. It is shown from simulation results that the achievable rates of proposed algorithms approach that of the AS scheme which is optimized by exhaustive search.

Scheduling for Multiuser MIMO Broadcast Systems: Transmit or Receive Beamforming?

In this paper, we present an approximation formula and the close-form expression for the sum rate of the transmit and the receive zero-forcing (ZF) multiple-input multiple-output (MIMO) broadcast systems with user selection, respectively. Instead of assuming a large number of users to obtain a scaling law as most current work, we derive the sum rate formulas of the ZF MIMO broadcast systems with a small number of scheduled users. By analysis and simulations, we find that when taking the variations of feedback channel into account, the receive ZF MIMO broadcast system is more robust to feedback errors and can deliver equal or even higher sum rate than the transmit ZF MIMO broadcast system. We discuss whether a feedback channel is suitable to send channel state information (CSI) for calculating transmit antenna beamforming weights, or suitable to send CSI for selecting users in the receive ZF MIMO broadcast system. Our results show that as the variation of feedback channel errors increases from 0.5 to 1.5, the receive ZF 3 × 3 MIMO broadcast system can provide 36% to 116% higher sum rate than the transmit ZF 3 × 3 MIMO broadcast system in the case of 20 users at signal to noise ratio (SNR) equal to 20 dB. Providing that more feedback bandwidth and an error-free feedback channel are available, the transmit ZF MIMO broadcast system can achieve higher sum rate than the receive ZF MIMO broadcast system.

Novel limited feedback scheme under the MIMO broadcast system

By deducing the distribution of the normalized channel covariance matrix, a novel limited feedback scheme is proposed under multiple users (MU) multiple-input multiple-output (MIMO) broadcast channel (BC) system. The proposed scheme has advantages in three aspects. First, it has no constraints on the number of users or antennas. Second, each user's feedback bits are independent of the number of receiving antennas. Third, the proposed scheme avoids the storage of large-size codebook on the transceivers. Simulation results show that the performance of the proposed scheme is close to the perfect channel state information (CSI) case and it just needs a small number of feedback bits.

Dynamic linear precoding for the exploitation of known interference in MIMO broadcast systems

This paper introduces a novel channel inversion (CI) precoding scheme for the downlink of phase shift keying (PSK)-based multiple input multiple output (MIMO) systems. In contrast to common practice where knowledge of the interference is used to eliminate it, the main idea proposed here is to use this knowledge to glean benefit from the interference. It will be shown that the system performance can be enhanced by exploiting some of the existent inter-channel interference (ICI). This is achieved by applying partial channel inversion such that the constructive part of ICI is preserved and exploited while the destructive part is eliminated by means of CI precoding. By doing so, the effective signal to interference-plus-noise ratio (SINR) delivered to the mobile unit (MU) receivers is enhanced without the need to invest additional transmitted signal power at the MIMO base station (BS). It is shown that the trade-off to this benefit is a minor increase in the complexity of the BS processing. The presented theoretical analysis and simulations demonstrate that due to the SINR enhancement, significant performance and throughput gains are offered by the proposed MIMO precoding technique compared to its conventional counterparts.

Low Complexity Antenna Selection Scheme for Multicarrier MIMO Broadcast Communication

A low complexity antenna selection scheme for multicarrier MIMO (Multiple Input Multiple Output) broadcast systems is proposed in this paper. Under special condition of single user in the system or when the number of subcarrier is only one, the system reduces to conventional MIMO-OFDM (Orthogonal Frequency Division Multiplexing) system or MIMO-BC (Broadcast Channel) system respectively. By analysing sub-optimal antenna selection schemes developed earlier for single user MIMO-OFDM systems and single carrier MIMO-BC systems, one can see many similarities which can be extended to multicarrier MIMO broadcast systems. The proposed method exploits these similarities to obtain a low complexity system design with acceptable performance. The performance of the proposed scheme is studied via extensive simulation, and the computational complexity involved is compared to the conventional scheme. A selection gain of approximately 0.5 b/s/Hz is shown to be achievable using only two out of three antennas, and the proposed scheme is able to achieve up to 90% of the gain. This is achieved at a complexity that is significantly lower than the conventional methods, hence the practical implementation of the proposed scheme can be justified.

Optimizing ZF Precoders for MIMO Broadcast Systems

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In this paper, we develop optimization techniques for linear zero-forcing (ZF) multiple-input multiple-output (MIMO) broadcast (BC) precoders. A computationally efficient technique based on QR-update algorithms for implementing this optimization is then proposed. The application of the proposed ZF precoders and decoders to both large and small (in terms of the number of users) systems is considered. It is also shown that the proposed optimization technique is robust, and performs very well with nonlinear Tomlinson--Harashima precoding. Both coded and uncoded performances are considered. </para>