For digital data transmission using an orthogonal frequency-division multiplexing (OFDM) over fading channels, the interchannel- interference (ICI) term caused by the Doppler spread is correlated with the desired signal term. Nonetheless, many researchers have assumed the ICI term to be uncorrelated with the desired signal term. In this paper, we present the symbol-error-rate (SER) performance for the M-quadratic amplitude-modulation OFDM systems over Ricean fading using the exact correlated ICI model. The results are then compared with the uncorrelated ICI results. We find that the two results present some differences. The differences tend to increase as the Ricean factor is increased.

For joint maximum-likelihood (ML) frequency tracking and channel estimation using orthogonal frequency-division multiplexing (OFDM) training blocks in OFDM communications over mobile wireless channels, a major difficulty is the local extrema or multiple-solution complication arising from the multidimensional log-likelihood function. To overcome this, we first obtain crude ML frequency-offset estimators using single-time-slot samples from the received time-domain OFDM block. These crude frequency estimators are shown to have unique closed-form solutions. We then optimally combine these crude frequency estimators in the linear-minimum-mean-square-error (LMMSE) sense for a more accurate solution. Finally, by alternatively updating the LMMSE frequency estimator and the ML channel estimator through adaptive iterations, we successfully avoid the use of a multidimensional log-likelihood function, hence obviating the complex task of global solution search and, meanwhile, achieve good estimation performance. Our estimators have mean square errors (MSEs) tightly close to Cramer-Rao bounds (CRBs) with a wide tracking range.

It is a general consensus that an orthogonal space-time block code can achieve full diversity, and due to its orthogonal nature, the multiple-input-multiple-output (MIMO) maximum-likelihood (ML) decoding metrics can be decoupled into single-input-single-output (SISO) ML metrics based on linear processing at the receiver, thus greatly reducing the decoding complexity. In fact, nonorthogonal codes also currently exist that can achieve better symbol-error-rate performance without rate reduction and complexity increase for correlated fading channels. In this paper, we show by detailed derivations that nonorthogonal linear space-time block codes can also be decoded by ML decoupling through receiver linear processing. Our derived expressions for the decoupled ML metrics automatically contain the design information for the receiver linear processors.

We present exact symbol error rate (SER) performance analysis for M-QAM OFDM systems over Ricean and Rayleigh fading is analyzed. Both slow and fast quasi-static fading as well as frequency-selective and -nonselective channels are considered.

We derive the symbol error probability (SEP) expressions for orthogonal space-time block codes with any form of generalized complex orthogonal design (GCOD) employing arbitrary rectangular quadratic-amplitude modulation signaling over correlative fading channels. By first decorrelating the physical branches into uncorrelated virtual branches, a general expression for the moment generating function of the received signal-to noise ratio (SNR) is obtained, from which the SEP is derived. The result can be applied to correlative fading channels with any form of Gaussian fading gains. Moreover, channels having joint fading models, as well as mixed channel powers, are considered. We also discover that, for certain GCOD codes, different information symbols may exhibit different SEPs. The above features are demonstrated by two GCOD examples used for simulations. Theoretical performance curves are compared with Monte Carlo simulated results in excellent agreement.