Power control and clustering in heterogeneous cellular networks

被引:4
|
作者
Driouch, Elmahdi [1 ]
Ajib, Wessam [2 ]
Assi, Chadi [1 ]
机构
[1] Concordia Univ, CIISE, Montreal, PQ, Canada
[2] Univ Quebec Montreal, Dept Comp Sci, Montreal, PQ, Canada
关键词
Heuristic algorithms; NP hard; Power allocation; Small cell networks; COGNITIVE RADIO NETWORKS; BLOCK-DIAGONALIZATION; COOPERATIVE NETWORKS; SPECTRUM MANAGEMENT; COALITIONAL GAMES; INTERFERENCE; MIMO; CHANNELS;
D O I
10.1007/s11276-016-1299-7
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Recently, it is widely believed that significant coverage and performance improvement can be achieved through the deployment of small cells in conjunction with the well-established macro cells. However, it is expected that the high density of base stations in such heterogeneous cellular networks will give rise to multiple design problems related to both co-tier (small-to-small) and cross-tier (between small and macro cells) interference. Fortunately, cooperation between base stations will play a major role to cope with these problems and hence to enhance the users' data rates. In this paper, we consider a two-tier cellular network comprised of a macro cell underlaid with multiple small cells where both co-tier and cross-tier interference are taken into account. We study the scenario where the small cell base stations seek to maximize a common objective by forming multiple clusters through cooperation. These base stations have also to allocate power to their associated users and, at the same time, control the total aggregate interference caused to the macro cell user which has to be kept below a threshold prefixed by the macro cell base station. We consider two utility functions: the overall sum rate of the small cell network and the minimum data rate of the small cell users. We formulate the studied problems as mixed integer nonlinear optimization problems and we discuss their NP hardness. Therefore, due to the complexity of finding the optimal solution, we design heuristic algorithms which resolves efficiently the tradeoff between computational complexity and performance. We show through simulations that the designed heuristics approach the optimal solution (obtained using the complex exhaustive search algorithm) with highly reduced computational complexity.
引用
收藏
页码:2509 / 2520
页数:12
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