Data for: Secondary Users Selection and Sparse Narrow-band Interference Mitigation in Cognitive Radio Networks

Spectrum scarcity is a critical problem that may reduce the effectiveness of wireless technologies and services. To address this problem, different spectrum management techniques have been proposed such as overlay cognitive radio (CR) where the unlicensed users can share the same spectrum with the licensed users. The main challenges in overlay CR networks are the identification and detection of the Primary User (PU) signals in a multi-source narrow-band interference (NBI) scenario. Therefore, in this paper, we investigate the performance of an orthogonal frequency division multiplexing (OFDM) overlay CR network with Secondary Users (SUs) and subcarriers selection schemes. Three approaches for SUs and subcarriers Selection named Direct, Distributed and Incremental selection techniques are proposed in this paper to increase the expected signal to interference and noise ratio based on full or partial knowledge of the channel state information (CSI). We also show that Distributed selection techniques provide all the SUs equal chances to be selected without affecting the selection diversity gain. General as well as simplified outage probability expressions are derived and extensive simulations are conducted to evaluate the performance of the proposed techniques and support the theoretical derivations. To accommodate more SUs, a new approach for asynchronous NBI estimation and mitigation in CR networks is investigated. Without any prior knowledge of the NBI characteristics and based on sparse signal recovery theory, the proposed approach allows the PU to exploit the sparsity of the SUs interference to recover it and approach the interference-free limit over practical ranges of NBI power levels.

频谱稀缺是制约无线技术与服务效能发挥的关键难题。为解决该问题，学界已提出多种频谱管理技术，例如重叠式认知无线电（overlay cognitive radio, CR）：在该技术框架下，非授权用户可与授权用户共享同一频谱资源。重叠式认知无线电网络面临的核心挑战之一，是多源窄带干扰（multi-source narrow-band interference, NBI）场景下的主用户（Primary User, PU）信号识别与检测任务。有鉴于此，本文针对配置次用户（Secondary Users, SUs）与子载波选择方案的正交频分复用（orthogonal frequency division multiplexing, OFDM）重叠式认知无线电网络的性能展开研究。本文提出三类面向次用户与子载波的选择方案，分别为直接选择、分布式选择与增量选择算法，旨在基于完整或部分信道状态信息（channel state information, CSI）提升预期信干噪比。研究表明，分布式选择算法可在不损失选择分集增益的前提下，为所有次用户提供均等的被选概率。本文推导了通用形式与简化形式的中断概率（outage probability）表达式，并通过大量仿真实验对所提算法的性能进行验证，同时佐证了理论推导的正确性。为容纳更多次用户，本文进一步研究了认知无线电网络中异步窄带干扰（asynchronous narrow-band interference, NBI）估计与抑制的新方法。该方法无需预先掌握窄带干扰的特性，仅基于稀疏信号恢复理论（sparse signal recovery theory），即可让主用户利用次用户干扰的稀疏性完成干扰恢复，在实际窄带干扰功率区间内逼近无干扰性能极限。