Special Issue: Multiple-Input Multiple-Output (MIMO) Communications

The idea of using multiple transmit and receive antennas in wireless communication systems is one of the most important breakthroughs in communication theory during the last decade. Popularly referred to as MIMO technology, this concept can greatly improve data throughput and link performance in wireless networks. In principle, a MIMO system can operate in, or anywhere between, one of the two possible modes. If the transmitter knows the channel, then one can use spatial beamforming techniques to steer RF energy in the direction of the receiver. On the other hand, if the transmitter does not know the channel, one can use space-time coding which effectively distributes the transmitted power uniformly in all directions, and in addition augments the data with structure that can be used to combat from fading dips. Sometimes, space-time coding methods are grouped into two categories: those that focus on throughput improvement (e.g. Bell-Labs layered space-time architecture, BLAST), and those that solely aim at improving link performance (including, most notably, orthogonal block coding and transmit diversity schemes); however, this classification is simplistic and many of the currently best known schemes do not fall under any of these two groups. Space-time coding, beamforming and their various combinations are becoming relatively well understood in the research community—as evidenced by the literal explosion of research papers and books (e.g. [1,2]) on the topic. Nevertheless, researchers are continuing to explore the more intricate aspects of combined coding over space and time. The goal of this special issue has been to collect a few edge-cutting, high-quality papers that not only capture the state-ofthe-art of the field but also highlight open problems and current research topics. We are delighted to present eight papers that survived a very competitive peer review process. Broadly speaking, the papers can be grouped into four categories: two papers that deal with coding for MIMO, two papers on MIMO channel modeling and simulation, two papers on signal processing for MIMO and finally two papers on crosslayer design for MIMO systems. The first paper, ‘Iterative receivers for coded MIMO signaling’, by Biglieri, Nordio and Taricco, is a tutorial on iterative (turbo) processing for systems that concatenate a GF(2) channel code with a complex-valued multidimensional (matrix) channel. The authors present the topic using a first-principle approach, and they also describe how iterative coding and demodulation for MIMO models work and how they can be analyzed by using EXIT charts, a powerful technique so far mostly used for ‘classical’ turbo coding. The next paper, ‘Improving the performance of coded FDFR multi-antenna systems with turbo-decoding’, by Wang, Ma and Giannakis, continues on the theme of iterative receiver structures. In this work, the authors show how full-rate full-diversity (FDFR) space-time block codes, developed by the authors in their previous work, can be efficiently combined with GF(2) channel coding. This paper provides valuable insight into the trade-off between performance and complexity involved in the choice of linear space-time block codes versus using powerful GF(2) codes and their combination. The third paper, by Patzold and Hogstad, ‘A spacetime channel simulator for MIMO channel based on the geometrical one-ring scattering model’ describes a narrowband MIMO channel simulator based on a geometric model, and evaluates its accuracy. This topic is certainly important, as MIMO channels in reality often have different characteristics than toy models used in purely theoretical studies. The fourth paper, ‘Performance of MIMO spatial multiplexing algorithms using indoor channel measurements and models’, is also on performance evaluation of MIMO systems in realistic environments. The authors,