Abstract—We consider jointly designing transceivers for multiple-input multiple-output (MIMO) communications. Assuming the availability of the channel state information (CSI) at the transmitter (CSIT) and receiver (CSIR), we propose a scheme that can decompose a MIMO channel, in a capacity lossless manner, into multiple subchannels with prescribed capacities, or equivalently, signal-to-interference-and-noise ratios (SINRs). We refer to this scheme as the tunable channel decomposition (TCD), which is based on the recently developed generalized triangular decomposition (GTD) algorithm and the closed-form representation of minimum mean-squared-error VBLAST (MMSE-VBLAST) equalizer. The TCD scheme is particularly relevant to the applications where independent data streams with different qualities-of-service (QoS) share the same MIMO channel. The TCD scheme has two implementation forms. One is the combination of a linear precoder and a minimum mean-squared-error VBLAST (MMSE-VBLAST) equalizer, which is referred to as TCD-VBLAST, and the other includes a dirty paper (DP) precoder and a linear equalizer followed by a DP decoder, which we refer to as TCD-DP. We also include the optimal code-division multiple-access (CDMA) sequence design as a special case in the framework of MIMO transceiver designs. Hence, our scheme can be directly applied to optimal CDMA sequence design, both in the uplink and downlink scenarios. Index Terms—Channel capacity, channel decomposition, dirty paper (DP) precoding, generalized triangular decomposition, joint transceiver design, multiple-input multiple-output (MIMO), optimal CDMA sequences, quality-of-service, VBLAST. I.

This letter considers optimum linear transceivers for MIMO channels under a general framework based on Schurconcave and Schur-convex cost functions, subject to shaping constraints on the transmit covariance matrix. Such constraints may be useful, for example, to impose spectral masks in cable systems, to control the power transmitted along certain directions in wireless systems, or to limit the dynamic range of the power amplifiers at the different transmit dimensions.

Abstract—Precoded spatial multiplexing systems with rate-limited feedback have been studied recently based on various precoder selection criteria. Instead of those based on indirect performance indicators, we in this paper propose a new criterion directly based on the exact bit error rate (BER) that is applicable to systems with linear receivers and rectangular/square quadrature-amplitude-modulation constellations. The BER criterion outperforms any other alternative in terms of optimizing the BER performance for an uncoded system with linear receivers. We then develop a precoder codebook construction method based on the generalized Lloyd algorithm from the vector quantization literature. This construction is not directly based on the BER criterion. Hence, it is suboptimal in the BER sense. However, relative to those currently available, our newfound codebooks improve considerably various minimum distances between any pair of codewords of the codebook. Finally, we analyze the BER-optimal precoder in the asymptotic case with infinite-rate feedback that amounts to perfect channel knowledge at the transmitter. The infinite-rate optimal precoder based on the BER criterion is drastically different from the counterparts with other criteria, and it leads to a benchmark performance for finite-rate precoded spatial multiplexing systems. We observe from numerical results that the BER performance of finite-rate feedback with suboptimal codebooks approaches quickly the benchmark performance of infinite-rate feedback. This suggests that i) the number of feedback bits in practical systems need not be large and ii) the room for performance improvement via further codebook optimization shrinks quickly as the codebook size increases. Index Terms—Finite-rate feedback, Lloyd algorithm, precoding, spatial multiplexing.

The benefits of using multiple antennas at both the transmitter and the receiver in a wireless system are well established. Multiple-input multiple-output (MIMO) systems enable a growth in transmission rate linear in the minimum of the number of antennas at either end [1][2]. MIMO techniques also enhance link reliability and

In this paper, we study the problem of estimating correlated multiple-input multiple-output (MIMO) channels in the presence of colored interference. The linear minimum mean square error (MMSE) channel estimator is derived and the optimal training sequences are designed based on the MSE of channel estimation. We propose an algorithm to estimate the long-term channel statistics in the construction of the optimal training sequences. We also design an efficient scheme to feed back the required information to the transmitter where we can approximately construct the optimal sequences. Numerical results show that the optimal training sequences provide substantial performance gain for channel estimation when compared with other training sequences.

Abstract — This paper addresses the problem of radar waveform design for target identification and classification. Both the ordinary radar with a single transmitter and receiver and the recently proposed multiple-input multiple-output (MIMO) radar are considered. A random target impulse response is used to model the scattering characteristics of the extended (nonpoint) target, and two radar waveform design problems with constraints on waveform power have been investigated. The first one is to design waveforms that maximize the conditional mutual information (MI) between the random target impulse response and the reflected waveforms given the knowledge of transmitted waveforms. The second one is to find transmitted waveforms that minimize the mean-square error (MSE) in estimating the target impulse response. Our analysis indicates that under the same total power constraint, these two criteria lead to the same solution for a matrix which specifies the essential part of the optimum waveform design. The solution employs water-filling to allocate the limited power appropriately. We also present an asymptotic formulation which requires less knowledge of the statistical model of the target. Index Terms — Multiple-input multiple-output (MIMO) radar, radar waveform design, identification, classification, extended radar targets, mutual information (MI), minimum meansquare error (MMSE), waveform diversity. I.

Abstract — This paper addresses the performance of bitinterleaved coded multiple beamforming (BICMB) with imperfect knowledge of beamforming vectors. Various wireless standards become equivalent to BICMB when they are operated in beamforming mode. In BICMB, the invariance of the precoding matrix under an arbitrary unitary transform widely studied in the literature is not applicable. On the other hand, the optimum precoder and detector are not unique because of invariance under a diagonal unitary transform. We propose an optimal Euclidean distortion measure and a new linear detector. In addition, a new codebook design is proposed via the generalized Lloyd algorithm based on the new distortion measure. We provide simulation results demonstrating the performance improvement achieved with the proposed distortion measure and the linear detector. I.

Abstract—This paper presents a method for jointly designing the transmitter–receiver pair in a block-by-block communication system that employs (intrablock) decision feedback detection. We provide closed-form expressions for transmitter–receiver pairs that simultaneously minimize the arithmetic mean squared error (MSE) at the decision point (assuming perfect feedback), the geometric MSE, and the bit error rate of a uniformly bit-loaded system at moderate-to-high signal-to-noise ratios. Separate expressions apply for the “zero-forcing ” and “minimum MSE” (MMSE) decision feedback structures. In the MMSE case, the proposed design also maximizes the Gaussian mutual information and suggests that one can approach the capacity of the block transmission system using (independent instances of) the same (Gaussian) code for each element of the block. Our simulation studies indicate that the proposed transceivers perform significantly better than standard transceivers and that they retain their performance advantages in the presence of error propagation. Index Terms—Bit error rate, block precoding, channel capacity, decision feedback detection, minimum mean-square error, mutual information, zero-forcing. I.

This paper addresses the joint design of transmit and receive beamvectors for a multicarrier MIMO channel within the general and powerful framework of convex optimization theory. From this perspective, a great span of design criteria can be easily accommodated and efficiently solved even though closedform expressions may not be available. Among other criteria, we consider the minimization of the average bit error rate (BER) and also of the maximum BER among all carriers for a given signal constellation. We show how to include additional constraints to control the Peak-to-Average Ratio (PAR) in the system design.

Abstract — Spatial multiplexing with multi-mode precoding provides a means to achieve both high capacity and high reliability in multiple-input multiple-output orthogonal frequencydivision multiplexing (MIMO-OFDM) systems. Multi-mode precoding uses linear transmit precoding that adapts the number of spatial multiplexing data streams or modes, according to the transmit channel state information (CSI). As such, it typically requires complete knowledge of the multi-mode precoding matrices for each subcarrier at the transmitter. In practical scenarios where the CSI is acquired at the receiver and fed back to the transmitter through a low-rate feedback link, this requirement may entail a prohibitive feedback overhead. In this paper, we propose to reduce the feedback requirement by combining codebook-based precoder quantization, to efficiently quantize and represent the optimal precoder on each subcarrier, and multi-mode precoder frequency down-sampling and interpolation, to efficiently reconstruct the precoding matrices on all subcarriers based on the feedback of the indexes of the quantized precoders only on a fraction of the subcarriers. To enable this efficient interpolation-based quantized multimode precoding solution, we introduce (1) a novel precoder codebook design that lends itself to precoder interpolation, across subcarriers, followed by mode selection, (2) a new precoder interpolator and, finally, (3) a clustered mode selection approach that significantly reduces the feedback overhead related to the mode information on each subcarrier. Monte-Carlo bit-error rate (BER) performance simulations demonstrate the effectiveness of the proposed quantized multi-mode precoding solution, at reasonable feedback overhead. Index Terms — Multiple-input multiple-output (MIMO), OFDM, limited feedback, vector quantization, mode selection, linear precoding, matrix interpolation under a unitary constraint. I.