Adaptive MIMO-OFDM Scheme with Reduced Computational Complexity and Improved Capacity

The general multidimensional linear channel model adequately represents a plethora of communication system models which utilize multidimensional transmit-receive signals for attaining increased rates and reliability in the presence of fading. The logarithmic dependence of the spectral efficiency of the transmitted power makes it extremely expensive to increase the capacity solely by radiating more power. Also, increasing the transmitted power in a mobile terminal is not advisable due to possible violation of regulatory power masks and possible electromagnetic radiation effects. Alternately, MIMO schemes if properly exploited can exhibit a linearly increasing capacity, due to the presence of a rich scattering environment that provides independent transmission paths from each transmit to each receive antenna. An Idealized practical communication system assumes perfect channel state information (CSI) and uses a linear transmitter to maximize the reliability of the wireless multi-antenna link. However, in actual practice the CSI is incomplete. As a result of this, there is a necessity to deal with ergodic and compound capacity formulations and these factors are strongly dependent on the model utilized to characterize the channel. Practical system models include quasi-static multiple-input multipleoutput (MIMO), MIMO-OFDM, ISI, amplify-andforward (AF), decode-and-forward (DF), and MIMO automatic repeat request (ARQ) models. Each of the above models introduces its own structure, its own error performance limits, and its own requirements on coding and decoding schemes. Finding general purpose transceiver structures with (provably) good performance in these scenarios, and with a reasonable computational complexity, is challenging. Existing MIMO systems are able to provide either high spectral efficiency (spatial multiplexing) or low error rate (high diversity) via exploiting multiple degrees of freedom available in the channel, but not both simultaneously as there is a fundamental tradeoff between the two. This diversity-multiplexing tradeoff (DMT) is best characterized using the concepts of multiplexing and diversity gains. Fundamentally, this is a tradeoff between the outage probabilities, i.e. the probability that the fading channel is not able to support the transmission rate. In this context, this work identifies a general, explicit non-random MIMO encoder-decoder structures and also guarantee optimal diversity-multiplexing trade-off and is an effective alternative to the computationally expensive Maximum Likelihood (M-L) receiver. The results obtained len