2014/01/07 by Hossein Shokri‐Ghadikolaei, Shokri-Ghadikolaei, Hossein, Carlo Fischione +1
Business, Management and Accounting · Computer Science · Engineering · #Advanced MIMO Systems Optimization #Advanced Queuing Theory Analysis #Age of Information Optimization #Cognitive Radio Networks and Spectrum Sensing #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Performance (cs.PF) #Probability (math.PR)
paper · pdf · doi:10.48550/arxiv.1401.1294
openalex publication_date 2014/01/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Developing an efficient spectrum access policy enables cognitive radios to\ndramatically increase spectrum utilization while ensuring predetermined quality\nof service levels for primary users. In this paper, modeling, performance\nanalysis, and optimization of a distributed secondary network with random\nsensing order policy are studied. Specifically, the secondary users create a\nrandom order of available channels upon primary users return, and then find\noptimal transmission and handoff opportunities in a distributed manner. By a\nMarkov chain analysis, the average throughputs of the secondary users and\naverage interference level among the secondary and primary users are\ninvestigated. A maximization of the secondary network performance in terms of\nthe throughput while keeping under control the average interference is\nproposed. It is shown that despite of traditional view, non-zero false alarm in\nthe channel sensing can increase channel utilization, especially in a dense\nsecondary network where the contention is too high. Then, two simple and\npractical adaptive algorithms are established to optimize the network. The\nsecond algorithm follows the variations of the wireless channels in\nnon-stationary conditions and outperforms even static brute force optimization,\nwhile demanding few computations. The convergence of the distributed algorithms\nare theoretically investigated based on the analytical performance indicators\nestablished by the Markov chain analysis. Finally, numerical results validate\nthe analytical derivations and demonstrate the efficiency of the proposed\nschemes. It is concluded that fully distributed sensing order algorithms can\nlead to substantial performance improvements in cognitive radio networks\nwithout the need of centralized management or message passing among the users.\n