In this paper, we study cooperative cognitive radio networks consisting of a primary user (PU) and multiple secondary users (SUs). SUs transmit only when PU is sensed as silent and may interfere with primary transmission due to imperfect sensing. When primary activity is sensed correctly, SUs cooperate with PU by assisting retransmission of failed packets of PU. We analyze packet throughput of PU and SU for three variations of the proposed cooperation method. A signal flow graph-based approach is employed to obtain the closed-form expressions of packet throughput. The analysis is done for two cases: individual sensing and cooperative sensing. Furthermore, we characterize the optimal transmission probability of SUs that maximizes individual secondary packet throughput keeping all queues in the system stable. Results present a comparison of throughput performance of the proposed cooperation methods under different scenarios and show their benefits for both PU and SU throughput.
@cite_0 studied throughput and average time for packet delivery in a non-cognitive network for two cooperation scenarios-- forced cooperation where best relay retransmits a failed packet and voluntary cooperation where a user may act as relay to get higher access probability in return. In our paper, due to presence of PU, relaying capability of SUs is affected by sensing errors and interference by other users. In @cite_0 , authors modelled packet transmission process of automatic repeat request (ARQ) mechanism as Markov chain assuming that at most one retransmission per packet is allowed. We model transmission process of proposed protocols in a similar way but the signal flow graph approach employed for throughput analysis puts no restriction on number of retransmissions.
@cite_0
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This paper introduces a novel technique for access by a cognitive Secondary User (SU) to a spectrum with an incumbent Primary User (PU), which uses Type-I Hybrid ARQ. The technique allows the SU to perform selective retransmissions of previously corrupted SU data packets. The temporal redundancy introduced by the primary ARQ protocol and by the selective SU retransmission process can be exploited by the SU receiver to perform Interference Cancellation (IC) over the entire interference pattern, thus creating a "clean" channel for the decoding of the concurrent message. The chain decoding technique, initiated by a successful decoding operation of a SU or PU message, consists in the iterative application of IC, as previously corrupted messages become decodable. Based on this scheme, we design an optimal policy that maximizes the SU throughput under a constraint on the average long-term PU throughput degradation. We show that the optimal policy can be found by first optimizing the SU access policy using a Markov Decision Process formulation, and then applying a chain decoding protocol defined by five basic rules. Such an approach enables a compact state representation of the protocol, and its efficient numerical optimization. Finally, we show by numerical results the throughput benefit of the proposed technique.