We present an analytical framework to assess the link layer throughput of multichannel Opportunistic Spectrum Access (OSA) ad hoc networks. Specifically, we focus on analyzing various combinations of collaborative spectrum sensing and Medium Access Control (MAC) protocol abstractions. We decompose collaborative spectrum sensing into layers, parametrize each layer, classify existing solutions, and propose a new protocol called Truncated Time Division Multiple Access (TTDMA) that supports efficient distribution of sensing results in “K out of N” fusion rule. In case of multichannel MAC protocols, we evaluate two main approaches of control channel design with 1) dedicated and 2) hopping channel. We propose to augment these protocols with options of handling secondary user (SU) connections preempted by primary user (PU) by 1) connection buffering until PU departure and 2) connection switching to a vacant PU channel. By comparing and optimizing different design combinations, we show that 1) it is generally better to buffer preempted SU connections than to switch them to PU vacant channels and 2) TTDMA is a promising design option for collaborative spectrum sensing process when K does not change over time.
Considering the final group of papers, when coupling spectrum sensing procedures with link layer protocols, there is a fundamental tradeoff between sensing time, sensing quality and OSA network throughput. This has been independently found for general OSA network models with a single sensing band @cite_42 , multiple sensing bands @cite_21 with and without cooperative detection and centralized resource allocation, and in a context of MAC protocol abstraction @cite_24 for a non-cooperative sensing case. See also recent discussion in [Sec. 2.3.1, 7.3, and 10.2.4] hossain_book_2009 . This tradeoff will be especially clear, while evaluating microscopic models, since the detection time creates a significant overhead for the data exchange phase. Recently the model of @cite_42 was extended to the case of @math out of @math '' rule in cooperative sensing @cite_52 , optimizing parameters of the model to maximize the throughput given detection rate requirements. Unfortunately, the delay caused by exchanging sensing information was not included.
@cite_24 @cite_52 @cite_42 @cite_21
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Sensing monitoring of spectrum-availability has been identified as a key requirement for dynamic spectrum allocation in cognitive radio networks (CRNs). An important issue associated with MAC-layer sensing in CRNs is how often to sense the availability of licensed channels and in which order to sense those channels. To resolve this issue, we address (1) how to maximize the discovery of spectrum opportunities by sensing-period adaptation and (2) how to minimize the delay in finding an available channel. Specifically, we develop a sensing-period optimization mechanism and an optimal channel-sequencing algorithm, as well as an environment- adaptive channel-usage pattern estimation method. Our simulation results demonstrate the efficacy of the proposed schemes and its significant performance improvement over nonoptimal schemes. The sensing-period optimization discovers more than 98 percent of the analytical maximum of discoverable spectrum-opportunities, regardless of the number of channels sensed. For the scenarios tested, the proposed scheme is shown to discover up to 22 percent more opportunities than nonoptimal schemes, which may become even greater with a proper choice of initial sensing periods. The idle-channel discovery delay with the optimal channel-sequencing technique ranges from 0.08 to 0.35 seconds under the tested scenarios, which is much faster than nonoptimal schemes. Moreover, our estimation method is shown to track time-varying channel-parameters accurately. In a cognitive radio network, the secondary users are allowed to utilize the frequency bands of primary users when these bands are not currently being used. To support this spectrum reuse functionality, the secondary users are required to sense the radio frequency environment, and once the primary users are found to be active, the secondary users are required to vacate the channel within a certain amount of time. Therefore, spectrum sensing is of significant importance in cognitive radio networks. There are two parameters associated with spectrum sensing: probability of detection and probability of false alarm. The higher the probability of detection, the better the primary users are protected. However, from the secondary users' perspective, the lower the probability of false alarm, the more chances the channel can be reused when it is available, thus the higher the achievable throughput for the secondary network. In this paper, we study the problem of designing the sensing duration to maximize the achievable throughput for the secondary network under the constraint that the primary users are sufficiently protected. We formulate the sensing-throughput tradeoff problem mathematically, and use energy detection sensing scheme to prove that the formulated problem indeed has one optimal sensing time which yields the highest throughput for the secondary network. Cooperative sensing using multiple mini-slots or multiple secondary users are also studied using the methodology proposed in this paper. Computer simulations have shown that for a 6 MHz channel, when the frame duration is 100 ms, and the signal-to-noise ratio of primary user at the secondary receiver is -20 dB, the optimal sensing time achieving the highest throughput while maintaining 90 detection probability is 14.2 ms. This optimal sensing time decreases when distributed spectrum sensing is applied. In cognitive radio networks, the performance of the spectrum sensing depends on the sensing time and the fusion scheme that are used when cooperative sensing is applied. In this paper, we consider the case where the secondary users cooperatively sense a channel using the k -out-of-N fusion rule to determine the presence of the primary user. A sensing-throughput tradeoff problem under a cooperative sensing scenario is formulated to find a pair of sensing time and k value that maximize the secondary users' throughput subject to sufficient protection that is provided to the primary user. An iterative algorithm is proposed to obtain the optimal values for these two parameters. Computer simulations show that significant improvement in the throughput of the secondary users is achieved when the parameters for the fusion scheme and the sensing time are jointly optimized. Opportunistic spectrum access (OSA) that allows secondary users to independently search for and exploit instantaneous spectrum availability is considered. The design objective is to maximize the throughput of a secondary user while limiting the probability of colliding with primary users. Integrated in the joint design are three basic components: a spectrum sensor that identifies spectrum opportunities, a sensing strategy that determines which channels in the spectrum to sense, and an access strategy that decides whether to access based on potentially erroneous sensing outcomes. This joint design is formulated as a constrained partially observable Markov decision process (POMDP), and a separation principle is established. The separation principle reveals the optimality of myopic policies for the design of the spectrum sensor and the access strategy, leading to closed-form optimal solutions. Furthermore, it decouples the design of the sensing strategy from that of the spectrum sensor and the access strategy, and reduces the constrained POMDP to an unconstrained one. Numerical examples are provided to study the tradeoff between sensing time and transmission time, the interaction between the physical layer spectrum sensor and the MAC layer sensing and access strategies, and the robustness of the ensuing design to model mismatch.