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In time-division multiple-access (TDMA) systems, the autonomy of portable handsets is a major constraint. We propose a new method, conditional equalization, which minimizes the power consumption due to equalization by equalizing only when it is most needed. At each time slot, the receiver estimates the need for equalization with a deterministic criterion. The proposed criteria use thresholds, chosen to provide a compromise between loss in performance and percentage of saved equalization. The performance of our method is theoretically analyzed for two-path Rayleigh fading channels and simulated for the recommended COST 207 channels. Conditional equalization can ensure a degradation in the average signal-to-noise ratio (SNR) , providing a fixed bit-error-rate (BER with an average SNR = 9 dB with systematic equalization), of less than 0.5 dB while providing a gain of 43% spared equalization for bad urban (BU), 62% for hilly terrain (HT), 79% for typical urban (TU), and 98% for rural area (RA) models, respectively. Conditional equalization is shown to greatly improve the autonomy of the receiver by drastically reducing the power consumption due to equalization, without a noticeable loss in the performance.

It is well known that convolutional codes can be optimally decoded by using the Viterbi Algorithm (VA). We propose a decoding technique where the VA is applied to identify the error vector rather than the information message. We previously focused on convolutional coders of rate ½ [4] [5]. Here we generalize the method to codes of any rate. We show that, with the proposed type of decoding, the exhaustive computation of a vast majority of state to state iterations is unnecessary. Hence, performance close to optimum is achievable with a significant reduction of complexity. The higher the SNR, the greater the improvement for reduction in complexity. For instance, for SNR greater than 3 dB, a five fold reduction in complexity for the computation of ACS (Add Compare Select) is achieved.