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Resource management for traffic imbalance problem in green cognitive radio networks

机译：绿色认知无线电网络中交通不平衡问题的资源管理

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The main goal of the cognitive radio network (CRN) is to provide high throughput and ubiquitous data access, but now it is focusing on energy-efficient green CRN. The energy consumption of CRN depends upon the total network time of cognitive users (CUs) and the unbalanced traffic load of CUs (when multiple CUs try to approach the same channel and their time and energy are wasted due to congestion). Hence, we design the channel decision models based on queuing priority for two different channel selection strategies, first probability-based channel selection strategy (PCSS) and second sensing-based channel selection strategy (SCSS). This model helps to calculate the optimum channel selection probability in PCSS and the optimum number of channels in the SCSS. With the help of the above-mentioned parameters, the total network time of CUs can be minimized, and their traffic load can be distributed among multiple applicant channels. We have considered the effects of PU's interruption and sensing errors (missed detection and false alarm) in our analysis. The result shows that, for heavy traffic load of CUs, the sensing-based strategy provides lesser network time, while for low traffic load, the probability-based strategy performs better. Next, we analyze the energy consumption at various operational modes in CRN and propose a channel sensing strategy that represents the energy-saving percentage for different conditions. The proposed strategies can minimize the total network time over 60% and energy consumption over 75% compared to the non-load balancing strategy. (C) 2021 Elsevier B.V. All rights reserved.
机译：认知无线电网络（CRN）的主要目标是提供高吞吐量和普遍存在的数据访问，但现在它专注于节能绿色CRN。 CRN的能量消耗取决于认知用户（CU）的总网络时间（CU）和CU的不平衡交通负荷（当多个CU尝试接近相同的信道时，由于拥塞而浪费）。因此，我们基于对两种不同信道选择策略的排队优先级设计频道决策模型，基于第一概率的信道选择策略（PCS）和基于第二感测的信道选择策略（SCS）。该模型有助于计算PC中的最佳通道选择概率以及SCS中的最佳通道数。在上述参数的帮助下，CU的总网络时间可以最小化，并且它们的交通负载可以分布在多个申请通道之间。我们考虑了PU的中断和传感错误（错过了检测和误报）的影响。结果表明，对于CU的繁重交通负荷，基于传感的策略提供更小的网络时间，而对于低流量负载，基于概率的策略更好地执行。接下来，我们在CRN中分析各种操作模式的能量消耗，并提出了一种通道传感策略，表示不同条件的节能百分比。与非负载平衡策略相比，拟议的策略可以最大限度地减少75％以上超过60％和能量消耗的总网络时间。 （c）2021 elestvier b.v.保留所有权利。

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