In cognitive radio systems,the design of spectrum sensing has to face the challenges of radio sensitivity and wide-band frequency agility. It is difficult for a single cognitive user to achieve timely and accurate wide-band spectrum sensing because of hardware limitations. However,cooperation among cognitive users may provide a way to do so. In this paper,we consider such a cooperative wide-band spectrum sensing problem with each of the cognitive users able to imperfectly sense only a small portion of spectrum at a time. The goal is to maximize the average throughput of the cognitive network,given the primary network's collision probability thresholds in each spectrum sub-band. The solution answers the essential questions:to what extent should each cognitive user cooperate with others and which part of the spectrum should the user choose to sense? An exhaustive search is used to find the optimal solution and a heuristic cooperative sensing algorithm is proposed to simplify the computational com-plexity. Inspired by this optimization problem,two practical cooperative sensing strategies are then presented for the centralized and distributed cognitive network respectively. Simulation results are given to demonstrate the promising performance of our proposed algorithm and strategies.
Rateless code usually generates a potentially infinite number of coded packets at the encoder and collects enough packets at the decoder to ensure reliable recovery of multiple information packets.The conventional rateless decoder usually works in a parallel manner which needs to initiate a new belief propagation (BP) decoding procedure upon each newly received collection of coded packets,thereby resulting in prohibitive decoding complexity in practice.In this paper,we present a novel serial decoding algorithm,i.e.,the serial storage belief propagation (SS BP) algorithm,for rateless codes over noisy channels.Specifically,upon receiving a new group of coded packets,the decoder initiates a new attempt to decode all the packets received so far,using the results of the previous attempt as initial input.Moreover,in each iteration of the new attempt,the decoder serially propagates the messages group by group from the most recent one to the earliest one.In this way,the newly updated messages can be propagated faster,expediting the recovery of information packets.In addition,the proposed serial decoding algorithm has significantly lower complexity than the existing parallel decoding algorithms.Simulation results validate its effectiveness in AWGN,Rayleigh,and Rician fading channels.
As a smart combination of cognitive radio networks and wireless sensor networks,recently introduced cognitive radio sensor network(CRSN) poses new challenges to the design of topology maintenance techniques for dynamic primary-user activities.This paper aims to provide a solution to the energy-efficient spectrum-aware CRSN clustering problem.Specifically,we design the clustered structure,establish a network-wide energy consumption model and determine the optimal number of clusters.We then employ the ideas from constrained clustering and propose both a centralized spectrum-aware clustering algorithm and a distributed spectrum-aware clustering(DSAC) protocol.Through extensive simulations,we demonstrate that DSAC can effectively form clusters under a dynamic spectrum-aware constraint.Moreover,DSAC exhibits preferable scalability and stability with its low complexity and quick convergence under dynamic spectrum variation.
