Topology Control for Maintaining Network Connectivity and Maximizing Network Capacity under the Physical Model
Topology Control for Maintaining Network Connectivity and Maximizing Network Capacity under the Physical Model
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DOI：
10.1109/infocom.2008.155
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发表时间：
2008-04
期刊：
影响因子：
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通讯作者：
Yan Gao;J. Hou;H. Nguyen
中科院分区：
文献类型：
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作者：
Yan Gao;J. Hou;H. Nguyen
本文以最大化网络容量为目标，研究了物理信干噪比(SINR)模型下的拓扑控制问题。研究表明，现有的基于图模型的拓扑控制在物理SINR模型下不能很好地捕获干扰，从而导致拓扑中的干扰较大，网络容量较低。为了弥补这一差距，我们提出了一种将功率控制算法T2P和拓扑控制算法P2T相结合的集中式方法，称为空间重用最大化(MaxSR)。T2P在给定固定拓扑的情况下优化发射功率的分配，其中，我们所说的最优化是指发射功率被如此分配，使得其最小化拓扑中的平均干扰程度(定义为可能干扰链路上正在进行的传输的干扰节点的数量)。另一方面，P2T基于在T2P中进行的功率分配，通过导出给出最小干扰程度的生成树来构建新的拓扑。通过交替调用这两种算法，功率分配可以快速收敛到最大化网络容量的运行点。我们形式化地证明了MaxSR的收敛性质。仿真结果表明，在最大化网络容量方面，MaxSR算法的性能比现有的拓扑控制算法提高了50%-110%。
In this paper we study the issue of topology control under the physical signal-to-interference-noise-ratio (SINR) model, with the objective of maximizing network capacity. We show that existing graph-model-based topology control captures interference inadequately under the physical SINR model, and as a result, the interference in the topology thus induced is high and the network capacity attained is low. Towards bridging this gap, we propose a centralized approach, called spatial reuse maximizer (MaxSR), that combines a power control algorithm T2P with a topology control algorithm P2T. T2P optimizes the assignment of transmit power given a fixed topology, where by optimality we mean that the transmit power is so assigned that it minimizes the average interference degree (defined as the number of interfering nodes that may interfere with the ongoing transmission on a link) in the topology. P2T, on the other hand, constructs, based on the power assignment made in T2P, a new topology by deriving a spanning tree that gives the minimal interference degree. By alternately invoking the two algorithms, the power assignment quickly converges to an operational point that maximizes the network capacity. We formally prove the convergence of MaxSR. We also show via simulation that the topology induced by MaxSR outperforms that derived from existing topology control algorithms by 50%-110% in terms of maximizing the network capacity.