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.
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The effect of full-duplex cooperative relaying in a random access multiuser network is investigated here. First, we model the self-interference incurred due to full-duplex operation, assuming multi-packet reception capabilities for both the relay and the destination node. Traffic at the source nodes is considered saturated and the cooperative relay, which does not have packets of its own, stores a source packet that it receives successfully in its queue when the transmission to the destination has failed. We obtain analytical expressions for key performance metrics at the relay, such as arrival and service rates, stability conditions, and average queue length, as functions of the transmission probabilities, the self interference coefficient, and the links' outage probabilities. Furthermore, we study the impact of the relay node and the self-interference coefficient on the per-user and aggregate throughput, and the average delay per packet. We show that perfect self-interference cancelation plays a crucial role when the SINR threshold is small, since it may result to worse performance in throughput and delay comparing with the half-duplex case. This is because perfect self-interference cancelation can cause an unstable queue at the relay under some conditions. Abstract In this work, we investigate a slotted-time relay assisted cooperative random access wireless network with multipacket (MPR) reception capabilities. MPR refers to the capability of a wireless node to successfully receive packets from more than two other modes that transmit simultaneously at the same slot. We consider a network of N saturated sources that transmit packets to a common destination node with the cooperation of two infinite capacity relay nodes. The relays assist the sources by forwarding the packets that failed to reach the destination. Moreover, the relays have also packets of their own to transmit to the destination. We further assume that the relays employ a state-dependent retransmission control mechanism. In particular, a relay node accordingly adapts its transmission probability based on the status of the other relay. Such a protocol is towards self-aware networks and leads to substantial performance gains in terms of delay. We investigate the stability region and the throughput performance for the full MPR model. Moreover, for the asymmetric two-sources, two-relay case we derive the generating function of the stationary joint queue-length distribution with the aid of the theory of boundary value problems. For the symmetric case, we obtain explicit expressions for the average queueing delay in a relay node without solving a boundary value problem. Extensive numerical examples are presented and provide insights on the system performance. Abstract In this work we analyze a novel queueing system for modeling cooperative wireless networks. We consider a network of three saturated source users, say a central and two background users, two relay nodes and a common destination node. When the central user fails to transmit a packet directly to the destination, it forwards a copy of the blocked packet at both relay nodes in order to exploit the spatial diversity they provide. Moreover, each relay node receives also blocked packets from a dedicated background user. Relay nodes assist source users by retransmitting their blocked packets to the destination. Due to the complex interdependence among relays, and the wireless interference, the retransmission rate of a relay is affected by the state of the other. We consider a three-dimensional Markov process, investigate its stability, and study its steady-state performance using the theory of boundary value problems. Explicit expressions for the expected delay in the symmetrical model, and a generalization to N > 2 relay nodes are also given. Numerical examples are obtained and show insights into the system performance. 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.