Inaki Berenguer

Adaptive MIMO antenna selection via discrete stochastic optimization

Recently it has been shown that it is possible to improve the performance of multiple-input multiple-output (MIMO) systems by employing a larger number of antennas than actually used and selecting the optimal subset based on the channel state information. Existing antenna selection algorithms assume perfect channel knowledge and optimize criteria such as Shannon capacity or various bounds on error rate. This paper examines MIMO antenna selection algorithms where the set of possible solutions is large and only a noisy estimate of the channel is available. In the same spirit as traditional adaptive filtering algorithms, we propose simulation based discrete stochastic optimization algorithms to adaptively select a better antenna subset using criteria such as maximum mutual information, bounds on error rate, etc. These discrete stochastic approximation algorithms are ideally suited to minimize the error rate since computing a closed form expression for the error rate is intractable. We also consider scenarios of time-varying channels for which the antenna selection algorithms can track the time-varying optimal antenna configuration. We present several numerical examples to show the fast convergence of these algorithms under various performance criteria, and also demonstrate their tracking capabilities.

Adaptive MIMO antenna selection

The performance of multiple-input multiple-output (MIMO) systems can be improved by employing a larger number of antennas than actually used and selecting the optimal subset based on the channel state information. Existing antenna selection algorithms assume perfect channel knowledge and optimize criteria such as Shannon capacity or various bounds on error rate. This paper examines MIMO antenna selection algorithms when the set of possible solutions is large and only a noisy estimate of the channel is available. We propose discrete stochastic approximation algorithms to adoptively select a better antenna subset using criteria such as maximum channel capacity, minimum error rate, etc. We also consider scenarios of time-varying channels for which the antenna selection algorithms can track the time-varying optimal antenna configuration. We present numerical examples to show the convergence of these algorithms and the excellent tracking capabilities.

MIMO antenna selection with lattice-reduction-aided linear receivers

A method to improve the performance of multiple-input-multiple-output systems is to employ a large number of antennas and select the optimal subset depending on the specific channel realization. A simple antenna-selection criterion is to choose the antenna subset that maximizes the mutual information. However, when the receiver has finite complexity decoders, this criterion does not necessarily minimize the error rate (ER). Therefore, different selection criteria should be tailored to the specific receiver implementation. In this paper, we develop new antenna-selection criteria to minimize the ER in spatial multiplexing systems with lattice-reduction-aided receivers. We also adapt other known selection criteria, such as maximum mutual information, to this specific receiver. Moreover, we consider adaptive antenna-selection algorithms when the channel is not perfectly known at the receiver but can only be estimated. We present simulation examples to show the ER of the different selection criteria and the convergence of the adaptive algorithms. We also discuss the difference in complexity and performance among them.

Space-time coding and signal processing for MIMO communications

Rapid growth in mobile computing and other wireless multimedia services is inspiring many research and development activities on high-speed wireless communication systems. Main challenges in this area include the development of efficient coding and modulation signal processing techniques for improving the quality and spectral efficiency of wireless systems. The recently emerged space-time coding and signal processing techniques for wireless communication systems employing multiple transmit and receive antennas offer a powerful paradigm for meeting these challenges. This paper provides an overview on the recent development in space-time coding and signal processing techniques for multiple-input multiple-output (MIMO) communication systems. We first review the information theoretic results on the capacities of wireless systems employing multiple transmit and receive antennas. We then describe two representative categories of space-time systems, namely, the BLAST system and the space-time block coding system, both of which have been proposed for next-generation high-speed wireless system. Signal processing techniques for channel estimation and decoding in space-time systems are also discussed. Finally, some other coding and signal processing techniques for wireless systems employing multiple transmit and receive antennas that are currently under intensive research are also briefly touched upon.

Lattice-reduction-aided receivers for MIMO-OFDM in spatial multiplexing systems

Orthogonal frequency division multiplexing (OFDM) significantly reduces receiver complexity in wireless systems with multipath propagation and therefore has recently been proposed for use in wireless broadband multi-antenna (MIMO) systems. The performance of the maximum likelihood (ML) detector in MIMO-OFDM system is optimal, however, its complexity is prohibitive. A number of other detectors, both linear and non-linear, may offer substantially lower complexity, however, their performance is significantly worse. This paper uses a class of lattice-reduction-aided (LRA) receivers for MIMO-OFDM systems with an arbitrary number of antennas that can achieve near maximum likelihood detector performance with low complexity. Performance comparisons between the LRA receiver and other popular receivers, including linear receivers and V-BLAST in both independent and correlated channels, are provided. It will be shown that the performance of the LRA receiver is superior to that achieved by sub-optimal detection methods, especially when the channel is correlated.

A simple baseband transmission scheme for power line channels

We propose a simple pulse-amplitude modulation (PAM)-based coded modulation scheme that overcomes two major constraints of power line channels, viz., severe insertion-loss and impulsive noise. The scheme combines low-density parity-check (LDPC) codes, along with cyclic random-error and burst-error correction codes to achieve high-spectral efficiency, low decoding complexity, and a high degree of immunity to impulse noise. To achieve good performance in the presence of intersymbol interference (ISI) on static or slowly time-varying channels, the proposed coset-coding is employed in conjunction with Tomlinson-Harashima precoding and spectral shaping at the transmitter. In Gaussian noise, the scheme performs within 2 dB of unshaped channel capacity at a bit-error rate (BER) of 10/sup -11/, even with (3,6)-regular LDPC codes of modest length (1000-2000 bits). To mitigate errors due to impulse noise (a combination of synchronous and asynchronous impulses), a multistage interleaver is proposed, each stage tailored to the error-correcting property of each layer of the coset decomposition. In the presence of residual ISI, colored Gaussian noise, as well as severe synchronous and asynchronous impulse noise, the gap to Shannon capacity of the scheme to a Gaussian-noise-only channel is 5.5 dB at a BER of 10/sup -7/.

Minimum Error-Rate Linear Dispersion Codes for Cooperative Relays

Cooperative diversity systems have recently been proposed as a solution to provide spatial diversity for terminals where multiple antennas are not feasible to be implemented. As in multiple-input-multiple-output systems, space-time codes can be used to efficiently exploit the increase in capacity provided in cooperative diversity systems. In this paper, we propose a two-layer linear dispersion (LD) code for cooperative diversity systems and derive a simulation-based optimization algorithm to optimize the LD code and power allocation in terms of block error rate. The proposed code design paradigm can obtain optimal codes under arbitrary fading statistics. Performance comparisons are made to other cooperative diversity schemes. The effect that distances between source, relays, and destination terminals have on the energy allocation between the broadcast and cooperative intervals is also studied. Cooperative diversity, gradient estimation, linear dispersion (LD) codes, multiple-input-multiple-output (MIMO), stochastic approximation.

Improved detection methods for MIMO-OFDM-CDM communication systems

We consider multiple input multiple output, orthogonal frequency division multiplexing, code division multiplexing (MIMO-OFDM-CDM) techniques for the efficient improvement of the link reliability/spectral efficiency of very high data rate communication systems. In particular, we apply MIMO detection methods based on lattice reduction, partial decision feedback (PDF), and BLAST ordering techniques to MIMO-OFDM-CDM systems. Simulation results show that the proposed receivers significantly outperform the conventional zero-forcing (ZF), minimum mean squared error (MMSE), and vertical Bell Labs layered space time (V-BLAST) receivers without severely compromising system complexity.

Efficient maximum-likelihood decoding of spherical lattice codes

A new framework for efficient exact maximum-likelihood (ML) decoding of spherical lattice codes is developed. It employs a double-tree structure: The first is that which underlies established tree-search decoders; the second plays the crucial role of guiding the primary search by specifying admissible candidates and is our present focus. Lattice codes have long been of interest due to their rich structure, leading to decoding algorithms for unbounded lattices, as well as those with axis-aligned rectangular shaping regions. Recently, spherical Lattice Space-Time (LAST) codes were proposed to realize the optimal diversity-multiplexing tradeoff of MIMO channels. We address the so-called boundary control problem arising from the spherical shaping region defining these codes. This problem is complicated because of the varying number of candidates to consider at each search stage; it is not obvious how to address it effectively within the frameworks of existing decoders. Our proposed strategy is compatible with all sequential tree-search detectors, as well as auxiliary processing such as the MMSEGDFE and lattice reduction. We demonstrate the superior performance and complexity profiles achieved when applying the proposed boundary control in conjunction with two current efficient ML detectors and show an improvement of 1dB over the state-of-the-art at a comparable complexity.

Linear Precoding Versus Linear Multiuser Detection in Downlink TDD-CDMA Systems

In this paper, we compare two classes of linear interference suppression techniques for downlink TDD-CDMA systems, namely, linear multiuser detection methods (receiver processing) and linear precoding methods (transmitter processing). For the linear precoding schemes, we assume that the channel state information (CSI) is available only at the transmitter but not at the receiver (i.e., ultra simple receivers). We propose several precoding techniques and the corresponding power control algorithms. The performance metric used in the comparisons is the total power required at the transmitter to achieve a target SINR at the receiver. Our results reveal that in general multiuser detection and precoding offer similar performance; but in certain scenarios (e.g, low BER requirements or use of random spreading sequences), precoding can bring a substantial performance improvement. These results motivate the use of precoding techniques to reduce the complexity of the system and the mobile terminals (only a matched-filter to the own spreading sequence is required without CSI). Moreover, it is shown that the proposed chip-wise linear MMSE precoding method is optimal in the sense that it requires the minimum total transmitted power to meet a certain receiver SINR performance.