The effects of system parameters upon the performance are quantified under the assumption that some statistical information of the wireless fading channels is available. These results are useful in determining the optimal design of system parameters. Suboptimal receivers are designed for systems that are constrained in terms of implementation complexity.
The achievable rates are investigated for a wireless communication system when neither the transmitter nor the receiver has prior knowledge of the channel state information (CSI). Quantitative results are provided for independent and identically distributed (i.i.d.) Gaussian signals. A simple, low-duty-cycle signaling scheme is proposed to improve the information rates for low signal-to-noise ratio (SNR), and the optimal duty cycle is expressed as a function of the fading rate and SNR. It is demonstrated that the resource allocations and duty cycles developed for Gaussian signals can also be applied to systems using other signaling formats.
The average SNR and outage probabilities are examined for amplify-and-forward cooperative relaying schemes in Rayleigh fading channels. Simple power allocation strategies are determined by using knowledge of the mean strengths of the channels.
Suboptimal algorithms are proposed for cases that optimal receivers are difficult to implement. For systems with multiple transmit antennas, an iterative method is used to avoid the inversion of a data-dependent matrix in decision-directed channel estimation. When CSI is not available, two noncoherent detection algorithms are formulated based on the generalized likelihood ratio test (GLRT). Numerical results are presented to demonstrate the use of GLRT-based detectors in systems with cooperative diversity
