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Energy-Efficient Spectrum Access in Cognitive Radios

机译:认知无线电中的节能频谱访问

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Cognitive radio (CR) and energy-efficient design have emerged as two promising techniques to achieve high spectrum efficiency (SE) and energy efficiency (EE), respectively. In this paper, we study energy-efficient opportunistic spectrum access strategies for an orthogonal frequency division multiplexing (OFDM)-based CR network with multiple secondary users (SUs). Both worst EE and average EE are considered and optimized for different emphases and application scenarios. Since the original optimization issues belong to nonconvex integer combinatorial fractional program and are essentially NP-hard for an optimal solution, we use continuous and convex relaxation to modify the problems for somewhat better mathematical tractability. For the relaxed worst-EE-based spectrum access problem, we first demonstrate the joint quasiconcavity of EE on subchannel and power allocation matrices and then develop a framework to find the optimal solution based on efficient root finding and convex optimization. We also develop a low-complexity alternative for suboptimal solution. The relaxed average-EE-based spectrum access problem is still NP-hard and may have many local optima. We first transform the problem into an equivalent form and introduce a general concave envelope based branch-and-bound (B&B) approach to find the global optimal solution. We then exploit the underlying properties of the energy-efficient transmission to speed up the convergence of the B&B approach. Besides, we develop a low-complexity heuristic approach to find a suboptimal solution. Simulation results show that the energy-efficient spectrum access strategies significantly boost EE compared with the conventional spectral-efficient spectrum access ones while the low-complexity suboptimal approaches can well balance the performance and complexity.
机译:认知无线电(CR)和节能设计已成为分别实现高频谱效率(SE)和能源效率(EE)的两种有前途的技术。在本文中,我们研究了基于正交频分复用(OFDM)的具有多个次级用户(SU)的CR网络的节能机会频谱访问策略。针对不同的重点和应用场景,考虑并优化了最差的EE和平均EE。由于最初的优化问题属于非凸整数组合小数程序,并且对于最优解本质上是NP难的,因此我们使用连续和凸松弛来修改问题,从而在数学上具有更好的易处理性。针对宽松的基于最差EE的频谱接入问题,我们首先在子信道和功率分配矩阵上证明EE的联合拟凹性,然后开发一个框架,在有效根查找和凸优化的基础上找到最优解。我们还为次优解决方案开发了一种低复杂度的替代方案。基于宽松的基于平均EE的频谱访问问题仍然是NP难题,并且可能具有许多局部最优解。我们首先将问题转换为等效形式,然后引入基于凹包络的常规分支定界(B&B)方法来找到全局最优解。然后,我们利用节能传输的基本属性来加快B&B方法的收敛速度。此外,我们开发了一种低复杂度的启发式方法来找到次优的解决方案。仿真结果表明,与传统的频谱高效频谱访问策略相比,节能频谱访问策略显着提高了EE,而低复杂度次优方法可以很好地平衡性能和复杂性。

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