The problem of designing codes with close-tocapacity performance on the multiple-input multiple-output (MIMO) quasi-static fading channel (QSFC) is addressed. We consider three different coding schemes -- namely, direct transmission of random-like codes, concatenation with linear processing orthogonal space-time block codes (o-STBC) and concatenation with space-time trellis codes (STTC). The constrained modulation outage capacity of each of these schemes is computed. It is shown how Low-density Parity Check (LDPC) codes may be used to approach capacity in these cases. For the STTC, the serial concatenation scheme of [1] turns out to have close to capacity performance.

Multiple-antennas constitute an effective mean to achieve spatial diversity in emerging bandwidth-efficient multiple -input multiple-output (MIMO) wireless systems. Until now, most contributions in this area are focused on the two limit cases of fully coherent and fully incoherent decoding, which, in turn, occur when perfect channel estimates and no channel estimates are available at the receiver. However, very accurate channel estimates typically demand long training sequences that reduces spectral efficiency. Therefore, testing capabilities of multiple-antenna systems with partially coherent decoding may be appealing for improving power-versus-bandwidth tradeoff. In this contribution, we focus on the optimized design and performance evaluations of multiple-antenna block-coded systems with partially-coherent maximum-likelihood (ML) decoding. After considering emerging fourth-generation WLANs (4GWLANs) as a possible application scenario, we present new performance bounds and optimized design criteria together with a new family of robust space-time unitary block codes that "self-match" to channel-estimation errors. We name these codes "self matching." Index Terms---Bandwidth-versus-power tradeoff, multiple-antenna, MIMO systems, partially coherent decoding, performance bounds, "self-matching" space-time block-codes, 4GWLAN.

The paper shows a procedure for evaluating the symmetric ergodic capacity of nonlinearly modulated finite alphabet signals in MIMO random channel. We first investigate informationally equivalent signal space representation for finite alphabet signals. The signals are allowed to be multidimensional per one antenna to reflect the modulation nonlinearity. The informationally equivalent signal space representation allows a factorization per one eigenmode (depending purely on one marginal eigenvalue) in the capacity evaluation in MIMO channel. The evaluation complexity does not depend on the MIMO dimensions. We consider two types of channel signals constraints. (1) A constraint on the waveform only. (2) A constraint on the waveform and memory (modeled as a Markov chain). The mean symmetric capacity for the former one is derived. For the latter one, we derive lower and upper bounds based on the entropy rate approximation.

In this paper, we focus on the throughput analysis, outage evaluation and optimized power allocation for Multiple -Input Multiple-Output (MIMO) pilot-based wireless systems subject to short-term constraints on the radiated power and equipped with a feedback-path for communicating back to the transmitter the imperfect MIMO channel estimates available at the receiver. The case of the ergodic throughput for Gaussian distributed input signals is analyzed, and the conditions for the (asymptotical) achievement of the Shannon capacity are pointed out. The main contributions of this work may be so summarized. First, we develop closed-form analytical expressions for the computation of the ergodic information throughput conveyed by the considered MIMO system for the case of ideal feedback link. Second, we present an iterative algorithm for the optimized power allocation over the transmit antennas that explicitly accounts for the imperfect MIMO channel estimates available at the receiver. Third, after relaxing the assumption of ideal feedback link, we test the sensitivity of the proposed power allocation algorithm on errors possibly introduced by the feedback channel, and then, we numerically evaluate the resulting throughput loss. Finally, we develop closed-form upper and lower bounds on the outage probability that are asymptotically tight.

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