2019/05/06 by Michal Yemini, Yemini, Michal, Goldsmith, Andrea J. · 1 citation
Computer Science · Engineering · #Advanced MIMO Systems Optimization #Cooperative Communication and Network Coding #FOS: Computer and information sciences #Information Theory (cs.IT) #Telecommunications and Broadcasting Technologies
paper · pdf · doi:10.48550/arxiv.1905.02891
openalex publication_date 2019/05/06 · openalex created_date 2020/07/23 · openalex updated_date 2026/07/28
This work presents a new network optimization framework for cellular networks\nusing neighborhood-based optimization. Under this optimization framework\nresources are allocated within virtual cells encompassing several base-stations\nand the users within their coverage areas. We form the virtual cells using\nhierarchical clustering with a minimax linkage criterion given a particular\nnumber of such cells. Once the virtual cells are formed, we consider an\ninterference coordination model in which base-stations in a virtual cell\njointly allocate the channels and power to users within the virtual cell. We\npropose two new schemes for solving this mixed integer NP-hard resource\nallocation problem. The first scheme transforms the problem into a continuous\nvariables problem; the second scheme proposes a new channel allocation method\nand then alternately solves the channel allocation problem using this new\nmethod, and the power allocation problem. We evaluate the average system sum\nrate of these schemes for a variable number of virtual cells. These results\nquantify the sum-rate along a continuum of fully-centralized versus\nfully-distributed optimization for different clustering and resource allocation\nstrategies. These results indicate that the penalty of fully-distributed\noptimization versus fully-centralized (cloud RAN) can be as high as 50%.\nHowever, if designed properly, a few base stations within a virtual cell using\nneighborhood-based optimization have almost the same performance as\nfully-centralized optimization.\n