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Swarm intelligence based Resource Allocation Algorithm for cognitive radio network

机译:基于群体的认知无线电网络资源分配算法

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In this paper, we propose a Swarm Intelligence based Resource Allocation Algorithm (SIRAA) for optimum allocation of available spectrum holes to cognitive radio users. Usage statistics reveal that large portion of the spectrum are under utilized due to stringent licensing policy. Spectrum utilization ranges from only 15% to 85% with a high variance in both temporal and spatial domain. Due to the inefficiency in the spectrum usage and increase in the access to the available limited spectrum in recent years, there is a need to access the existing wireless spectrum opportunistically. This new networking paradigm is referred as Cognitive radio networks. We used existing bidding strategy to allocate channels to cognitive radio users. A cognitive radio sends bid values (the bid value is a function of bandwidth requirement, bit error rate, possible interference, user type etc.) for every available spectrum holes to the base station. The base station allocates the spectrum band to the cognitive user by maximizing the totald bid value received from all cognitive users. We consider four different cases of allocation such that each cognitive user (i) will get exactly one channel (ii) will get channels in a proportionate manner (iii) will get at least k number of channels and (iv) will get at least k1 and at most k2 number of channels. We proposed a binary particle swarm optimization (PSO) technique to find an optimum allocation of channels to all cognitive users for all four cases. We compared our simulation results with traditional Hungarian method wherever the later is used to verify in some feasible cases.
机译:在本文中,我们提出了一种基于智能基于智能的资源分配算法(Siraa),用于最佳地将可用频谱孔分配给认知无线电用户。用法统计显示,由于严格的许可政策,利用了大部分频谱。频谱利用率仅为15%至85%,在时间和空间域中具有高方差。由于频谱使用的效率低,近年来对可用有限频谱的访问增加,需要有必要机会访问现有的无线频谱。这种新的网络范例称为认知无线电网络。我们使用现有的招标策略将渠道分配给认知无线电用户。认知无线电发送出价值(BID值是用于基站的每个可用频谱孔的带宽要求,钻头错误率,可能的干扰,用户类型等)。基站通过最大化从所有认知用户接收的TONTGLED出价值来分配频谱频带到认知用户。我们考虑四个不同的分配情况,使得每个认知用户(i)将恰好一个通道(ii)将以比例方式(iii)获得通道(iii)将获得至少k个频道数量,并且(iv)将获得至少k1并且在大多数K2的渠道数量。我们提出了二进制粒子群优化(PSO)技术,以找到所有四种情况的所有认知用户的最佳通道分配。我们将模拟结果与传统的匈牙利方法进行了比较,无论何时用于验证某些可行的情况。

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