Low-complexity and approximative sphere decoding of sparse signals

Multiuser detection can be implemented at the sink of a sensor network to receive the various signals of its sensor nodes. This is a viable approach as long as the number of sensor nodes is small. In case of many nodes, decoding can be considered technically infeasible, but assuming low transmission activities, the sparse nature of the sensor signals can be utilized. In this paper, we propose a sphere decoding algorithm to perform maximum likelihood decoding based on an extended distance metric that takes the a priori probability into account. By intentionally violating the ideal check of the sphere constraint, many improbable transmit hypotheses can be dismissed early, thus reducing decoding complexity but without notable loss of quality.