Opportunistic spectrum access (OSA) is a key technique enabling the secondary users (SUs) in a cognitive radio (CR) network to transmit over the "spectrum holes" unoccupied by the primary users (PUs). In this paper, we focus on the OSA design in the presence of reactive PUs, where PU's access probability in a given channel is related to SU's past access decisions. We model the channel occupancy of the reactive PU as a 4-state discrete-time Markov chain. We formulate the optimal OSA design for SU throughput maximization as a constrained finite-horizon partially observable Markov decision process (POMDP) problem. We solve this problem by first considering the conventional short-term conditional collision probability (SCCP) constraint. We then adopt a long-term PU throughput (LPUT) constraint to effectively protect the reactive PU transmission. We derive the structure of the optimal OSA policy under the LPUT constraint and propose a suboptimal policy with lower complexity. Numerical results are provided to validate the proposed studies, which reveal some interesting new tradeoffs between SU throughput maximization and PU transmission protection in a practical interaction scenario.
Most existing work on OSA with time-slotted PUs, including the aforementioned one, has assumed a PU model, where PU's transmission over a particular channel evolves as a 2-state on off Markov chain with fixed state transition probabilities. Similar assumptions can also be found in the experimental based work on OSA with unslotted PUs, such as @cite_15 and @cite_5 . Although greatly simplifying the OSA design, the non-reactive PU model might not be practical since existing wireless systems are mostly intelligent enough to adapt their transmissions upon experiencing collision or interference. For example, a PU may increase transmit power to compensate the link loss due to the received interference. Alternatively, it may reduce the channel access probability when collision occurs in a carrier sensing multiple access (CSMA) based primary system. In this paper, we refer to such PUs as PUs, to differentiate from their non-reactive counterparts.
@cite_5 @cite_15
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Because of the asynchronization between primary and secondary wireless networks, the synchronization between primary users (PUs) and secondary users (SUs) can be hardly guaranteed in nontime-slotted cognitive radio networks (CRNs). In this paper, we propose a novel framework for multichannel nontime-slotted CRNs, where the PUs randomly access and leave the licensed channels. Since the PUs cannot distinguish between primary and secondary signals, the PUs may sense a busy channel when the PUs start to reactivate during the SUs' transmission, thus generating a collision or entering the backoff stage. To guarantee the high-throughput transmission of the PUs and increase the channel utilization of the SUs, in this paper, we propose the wireless full-duplex spectrum sensing (FD-SS) scheme for SUs in multichannel nontime-slotted CRNs. Using our developed FD-SS scheme, the SUs can timely sense the PUs' reactivation during the same time when the SUs are transmitting their signals. Then, based on our proposed wireless FD-SS scheme, we further develop and analyze the wireless full-duplex cognitive medium access control (FDC-MAC) protocol for multichannel nontime-slotted CRNs. We conduct extensive numerical analyses, showing that our developed FD-SS scheme and FDC-MAC protocol can efficiently guarantee the high-throughput transmission of the PUs and increase the channel utilization of the SUs without requiring the synchronization between the PUs and the SUs over the multichannel nontime-slotted CRNs. In this paper, we investigate the joint optimal sensing and distributed Medium Access Control (MAC) protocol design problem for cognitive radio (CR) networks. We consider both scenarios with single and multiple channels. For each scenario, we design a synchronized MAC protocol for dynamic spectrum sharing among multiple secondary users (SUs), which incorporates spectrum sensing for protecting active primary users (PUs). We perform saturation throughput analysis for the corresponding proposed MAC protocols that explicitly capture the spectrum-sensing performance. Then, we find their optimal configuration by formulating throughput maximization problems subject to detection probability constraints for PUs. In particular, the optimal solution of the optimization problem returns the required sensing time for PUs' protection and optimal contention window to maximize the total throughput of the secondary network. Finally, numerical results are presented to illustrate developed theoretical findings in this paper and significant performance gains of the optimal sensing and protocol configuration. For achieving optimized spectrum usage, most existing opportunistic spectrum sensing and access protocols model the spectrum sensing and access problem as a partially observed Markov decision process by assuming that the information states and or the primary users' (PUs) traffic statistics are known a priori to the secondary users (SUs). While theoretically sound, the existing solutions may not be effective in practice due to two main concerns. First, the assumptions are not practical, as before the communication starts, PUs' traffic statistics may not be readily available to the SUs. Second and more serious, existing approaches are extremely vulnerable to malicious jamming attacks. By leveraging the same statistic information and stochastic dynamic decision-making process that the SUs would follow, a cognitive attacker with sensing capability can sense and jam the channels to be accessed by SUs, while not interfering PUs. To address these concerns, we formulate the antijamming, multichannel access problem as a nonstochastic multi-armed bandit problem. By leveraging probabilistically shared information between the sender and the receiver, our proposed protocol enables them to hop to the same set of channels with high probability while gaining resilience to jamming attacks without affecting PUs' activities. We analytically show the convergence of the learning algorithms and derive the performance bound based on regret . We further discuss the problem of tracking the best adaptive strategy and characterize the performance bound based on a new regret . Extensive simulation results show that the probabilistic spectrum sensing and access protocol can overcome the limitation of existing solutions and is highly resilient to various jamming attacks even with jammed acknowledgment (ACK) information. We venture beyond the "listen-before-talk" strategy that is common in many traditional cognitive radio access schemes. We exploit the bi-directional nature of most primary communication systems. By intelligently choosing their transmission parameters based on the observation of primary user (PU) communications, secondary users (SUs) in a cognitive network can achieve higher spectrum usage while limiting their interference to the PU. Specifically, we propose that the SUs listen to the PU's feedback channel to assess their interference on the primary receiver (PU-Rx), and adjust radio power accordingly to satisfy the PU's interference constraint. We investigate both centralized and distributed power control algorithms without active PU cooperation. We show that the PU feedback information inherent in many two-way primary systems can be used as important coordination signal among multiple SUs to distributively achieve a joint performance guarantee on the primary receiver's quality of service.