2014/09/10 by Sami Akın, Akin, Sami, M. Cenk Gursoy +1
Computer Science · #Cognitive Radio Networks and Spectrum Sensing #Wireless Communication Networks Research #Distributed Sensor Networks and Detection Algorithms
paper · pdf · doi:10.48550/arxiv.1409.3126
In cognitive radio systems, employing sensing-based spectrum access\nstrategies, secondary users are required to perform channel sensing in order to\ndetect the activities of primary users. In realistic scenarios, channel sensing\noccurs with possible errors due to miss-detections and false alarms. As another\nchallenge, time-varying fading conditions in the channel between the secondary\ntransmitter and the secondary receiver have to be learned via channel\nestimation. In this paper, performance of causal channel estimation methods in\ncorrelated cognitive radio channels under imperfect channel sensing results is\nanalyzed, and achievable rates under both channel and sensing uncertainty are\ninvestigated. Initially, cognitive radio channel model with channel sensing\nerror and channel estimation is described. Then, using pilot symbols, minimum\nmean square error (MMSE) and linear-MMSE (L-MMSE) estimation methods are\nemployed at the secondary receiver to learn the channel fading coefficients.\nExpressions for the channel estimates and mean-squared errors (MSE) are\ndetermined, and their dependencies on channel sensing results, and pilot symbol\nperiod and energy are investigated. Since sensing uncertainty leads to\nuncertainty in the variance of the additive disturbance, channel estimation\nstrategies and performance are interestingly shown to depend on the sensing\nreliability. It is further shown that the L-MMSE estimation method, which is in\ngeneral suboptimal, performs very close to MMSE estimation. Furthermore,\nassuming the channel estimation errors and the interference introduced by the\nprimary users as zero-mean and Gaussian distributed, achievable rate\nexpressions of linear modulation schemes and Gaussian signaling are determined.\nSubsequently, the training period, and data and pilot symbol energy allocations\nare jointly optimized to maximize the achievable rates for both signaling\nschemes.\n