Evaluation of Dynamic Channel and Power Assignment for Cognitive Networks
作者： Juan D. Deaton , Syed A. Ahmad , Umesh Shukla , Ryan E. Irwin , Luiz A. DaSilva
DOI: 10.1007/S11277-010-0003-Y
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摘要: In this paper, we develop a unifying optimization formulation to describe the Dynamic Channel and Power Assignment (DCPA) problem an evaluation method for comparing DCPA algorithms. refers allocation of transmit power frequency channels links in cognitive network so as maximize total number feasible while minimizing aggregate power. We apply our five representative DPCA algorithms proposed literature. This comparison illustrates tradeoffs between control modes (centralized versus distributed) channel/power assignment techniques. estimate complexity each algorithm. Through simulations, evaluate effectiveness achieving link allocations network, their efficiency. Our results indicate that, when few are available, all is comparable thus one with smallest should be selected. The Least Interfering Iterative algorithm does not require cross-link gain information, has overall lowest run time, achieves highest feasibility ratio distributed algorithms; however, comes at cost higher average per link.
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