Cluster-Based Fair Allocation Algorithm for Multi-Relay Single Carrier Distributed Networks

In this paper, we investigate a novel Random-based Fair-Allocation Fuzzy Comprehensive Evaluation- based Strategy with Relay Clustering (RFRC) for dual-hop Single- Carrier Frequency-Domain Equalization (SC-FDE) in cooperative systems with multiple relays and amplify-and- forward (AF) relaying. We address the problem of fair resource allocation for SC-FDE minimum mean square error (MMSE) receivers. In particular, relays are classified into multiple disjoint clusters through the K-means algorithm, where each cluster is identified by a centroid. The centroids of the clusters are directly related to the average amount of resources available to the relays belonging to that cluster, as well as the quality of the relaying´ links. The final centroids of the clusters after the convergence of the K-means algorithm, are used to generate contribution factors for each group. Different sub-channels are further associated with uniform random distribution where the thresholds of the uniform random variables are associated with the cluster´s contribution factors. RFRC for SC-FDE proves superior SER performance as well as improved diversity gain which is achieved by randomizing the allocation. The employed algorithm further improves the performance by optimizing the number of clusters. Numerical results are provided to corroborate the mathematical modeling.