2019/05/06 by Michal Yemini, Yemini, Michal, Goldsmith, Andrea J.
Computer Science · Engineering · #Advanced MIMO Systems Optimization #Advanced Wireless Network Optimization #Cooperative Communication and Network Coding #FOS: Computer and information sciences #Information Theory (cs.IT)
paper · pdf · doi:10.48550/arxiv.1905.02184
openalex publication_date 2019/05/06 · openalex created_date 2021/07/05 · openalex updated_date 2026/07/28
This work presents a new resource allocation optimization framework for\ncellular networks using neighborhood-based optimization. Under this\noptimization framework resources are allocated within virtual cells\nencompassing several base-stations and the users within their coverage area.\nIncorporating the virtual cell concept enables the utilization of more\nsophisticated cooperative communication schemes such as coordinated multi-point\ndecoding. We form the virtual cells using hierarchical clustering given a\nparticular number of such cells. Once the virtual cells are formed, we consider\na cooperative decoding scheme in which the base-stations in each virtual cell\njointly decode the signals that they receive. We propose an iterative solution\nfor the resource allocation problem resulting from the cooperative decoding\nwithin each virtual cell. Numerical results for the average system sum rate of\nour network design under hierarchical clustering are presented. These results\nindicate that virtual cells with neighborhood-based optimization leads to\nsignificant gains in sum rate over optimization within each cell, yet may also\nhave a significant sum-rate penalty compared to fully-centralized optimization.\n