A fuzzy approach for multiple-receiver digital communication systems with data fusion

Many multiple-receiver diversity schemes employ hard decisions combining rules to achieve a diversity gain in digital communications. In this paper, a fuzzy combining approach in diversity systems is proposed. The confidence levels associated with the local receiver soft-decisions are modeled by means of fuzzy membership functions. The reliabilities of the local receivers are weighted by the soft-decision confidence levels and fused in a central digital receiver to decide which symbol was transmitted. The performance of the proposed approach is evaluated and compared to the performance of optimal diversity, majority voting, optimal partial decision, and selection diversity in case of binary noncoherent frequency shift keying on a Rayleigh faded additive white Gaussian noise channel. It is shown that the proposed approach achieves considerable improvement over optimal partial decision, majority voting, and selection diversity when two bits per local receiver soft-decisions are used. It is also shown that three- or four-bit quantization is appropriate to achieve a performance comparable to the optimal diversity scheme.