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arXiv 1404.1995cs.NI
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认知无线电网络中吞吐量最大化的信道分配

Channel assignment for throughput maximization in cognitive radio networks

Le Thanh Tan, Long Bao Le

摘要:

在本文中,我们考虑在认知无线电网络的吞吐量最大化与硬件约束的次级用户的信道分配问题。具体来说,我们假设次要用户利用一组信道上的频谱漏洞,其中每个次要用户可以使用最多一个可用信道进行通信。我们开发了两种信道分配算法,可以有效地利用这些信道上的频谱机会。在第一种算法中,次级用户被分配不同的信道集合。我们表明,该算法实现了最大的吞吐量限制,如果信道的数量是足够大的。此外,我们提出了一种重叠信道分配算法,与非重叠信道分配算法相比,可以提高吞吐量性能。此外,我们设计了一个分布式的MAC协议的接入竞争的解决方案,并集成派生的MAC协议的开销到第二个信道分配算法。最后,数值结果验证了理论结果,并说明了由于重叠信道分配算法的性能增益。

英文摘要:

In this paper, we consider the channel allocation problem for throughput maximization in cognitive radio networks with hardware-constrained secondary users. Specifically, we assume that secondary users exploit spectrum holes on a set of channels where each secondary user can use at most one available channel for communication. We develop two channel assignment algorithms that can efficiently utilize spectrum opportunities on these channels. In the first algorithm, secondary users are assigned distinct sets of channels. We show that this algorithm achieves the maximum throughput limit if the number of channels is sufficiently large. In addition, we propose an overlapping channel assignment algorithm, that can improve the throughput performance compared to the non-overlapping channel assignment algorithm. In addition, we design a distributed MAC protocol for access contention resolution and integrate the derived MAC protocol overhead into the second channel assignment algorithm. Finally, numerical results are presented to validate the theoretical results and illustrate the performance gain due to the overlapping channel assignment algorithm.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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