Codeword optimization for uplink CDMA dispersive channels

Abstract

Abstract-We present the application of greedy interference avoidance methods to codeword optimization in the uplink of a code division multiple access (CDMA) system in which the channel between a given user and the base station receiver is assumed known and stable for the duration of the transmission. Repeated application of greedy interference avoidance monotonically increases sum capacity and yields an optimal codeword ensemble that satisfies a simultaneous water-filling distribution. However, algorithms for codeword optimization based on the greedy interference avoidance procedure are in general different from waterfilling schemes. We illustrate the algorithms with examples and look at properties of optimal codeword ensembles.Index Terms-CDMA, codeword adaptation, distributed interference avoidance, sum capacity optimization.

An overview of limited feedback in wireless communication systems

“…Another interesting area is signature optimization using limited feedback (e.g., [20], [248], [249], [256], [257], [263], [264], [328], [332], [341]). In fact, spreading code design using randomly generated codes formed the basis behind the development of RVQ ideas [281].…”

On the uplink-downlink duality for Gaussian vector channels with colored noise and applications to CDMA transmitter adaptation

“…We note that while many algorithms are available for obtaining uplink CDMA codewords (see [10][11][12][13] and references therein) only a few algorithms have been proposed for downlink scenarios [14][15][16]. We also note that the uplink CDMA codeword ensembles can be designed to optimize various performance measures such as individual or sum rates and Signal-to-Interference+Noise-Ratios (SINR).…”

“…,pK } which maximizes the sum capacity of the corresponding vector MAC. For general scenarios with non-ideal channels and colored noise, these may be obtained by applying the interference avoidance algorithms discussed in [11][12][13], and the corresponding uplink transmit covariance for a given user in this case is given by…”

Interference avoidance for wireless systems

“…d. Adjust user k's codewords sequentially using the greedy procedure of the basic eigen-algorithm; the codeword corresponding to symbol m of user k is replaced by the minimum eigenvector of the autocorrelation matrix of the corresponding interference-plus-noise process. e. Iterate the previous step until convergence (making use of escape methods [22] if the procedure stops in suboptimal points). 3.…”