MMC-DIA: multi-metric clustering with differential interference alignment for improving small cell performance

Abstract

Interference in small cells occurs due to the interoperability of different wireless communication technologies. Uncontrolled interference defaces the increasing user density and subscriber services. Therefore, interference management is mandatory to balance user service and performance enhancements. In this paper, multi-metric clustering with differential interference alignment (MMC-DIA) for leveraging the performance of small cell users is presented. This proposed technique operates in two phases namely clustering and differential interference alignment. In the clustering process, sum-rate maximization objective based grouping of small cell users is performed to retain the efficiency of communication. In a differential IA phase, the transmitted signal is analyzed for its first and second order of assessment on the basis of transmitter–receiver communication interval. Pre-coding and cancellation matrix over the signal vectors are imposed in the periodic time intervals for improving the degree of freedom (DoF) and thereby retaining the efficiency of the system. This is applicable for both the first and second order signal derivatives to handle inter and intra cluster interference along with the objective satisfaction. The performance of the proposed technique is compared for sum-rate, spectral efficiency, and DoF with the existing methods and non-clustering method respectively. From the comparative analysis, the proposed MMC-DIA is found to improve spectral efficiency and sum rate by 6.84% and 11.18% respectively. Similarly, with respect to the varying transmit power, the proposed MMC-DIA achieves 5.85% and 6.292% better spectral efficiency and sum rate.