text: 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.
  @cite_48: We analyze the performance of a wireless system consisting of a set of secondary users opportunistically sharing bandwidth with a set of primary users over a coverage area. The secondary users employ spectrum sensing to detect channels that are unused by the primary users and hence make use of the idle channels. If an active secondary user detects the presence of a primary user on a given channel, it releases the channel and switches to another idle channel, if one is available. In the event that no channel is available, the call waits in a buffer until either a channel becomes available or a maximum waiting time is reached. Spectrum sensing errors on the part of a secondary user cause false alarm and mis-detection events, which can potentially degrade the quality-of-service experienced by primary users. We derive system performance metrics of interest such as blocking probabilities. Our results suggest that opportunistic spectrum sharing can significantly improve spectrum efficiency and system capacity, even under unreliable spectrum detection. The proposed model and analysis method can be used to evaluate the performance of future opportunistic spectrum sharing systems.
  @cite_55: We develop a general framework for analyzing the performance of an opportunistic spectrum sharing (OSS) wireless system at the session level with Markovian arrivals and phasetype service times. The OSS system consists of primary or licensed users of the spectrum and secondary users that sense the channel status and opportunistically share the spectrum resources with the primary users in a coverage area. When a secondary user with an active session detects an arrival of a primary session in its current channel, the secondary user leaves the channel quickly and switches to an idle channel, if one is available, to continue the session. Otherwise, the secondary session is preempted and moved to a preemption queue. The OSS system is modeled by a multi-dimensional Markov process. We derive explicit expressions for the related transition rate matrices using matrix-analytic methods. We also obtain expressions for several performance measures of interest, and present both analytic and simulation results in terms of these performance measures. The proposed OSS model encompasses a large class of specific models as special cases, and should be useful for modeling and performance evaluation of future opportunistic spectrum sharing systems.
  @cite_6: A Markov chain analysis for spectrum access in licensed bands for cognitive radios is presented and forced termination probability, blocking probability and traffic throughput are derived. In addition, a channel reservation scheme for cognitive radio spectrum handoff is proposed. This scheme allows the tradeoff between forced termination and blocking according to QoS requirements. Numerical results show that the proposed scheme can greatly reduce forced termination probability at a slight increase in blocking probability
  @cite_39: A new loss model for cognitive radio spectrum access with finite user population are presented, and exact solution for the model and its approximation for computation scalability are given. Our model provides the investigation of the delay performance of a cognitive radio system. We study the delay performance of a cognitive radio system under various primary traffic loads and spectrum band allocations.
  @cite_15: Cognitive radio wireless networks is an emerging communication paradigm to effectively address spectrum scarcity challenge. Spectrum sharing enables the secondary unlicensed system to dynamically access the licensed frequency bands in the primary system without any modification to the devices, terminals, services and networks in the primary system. In this paper, we propose and analyze new dynamic spectrum access schemes in the absence or presence of buffering mechanism for the cognitive secondary subscriber (SU). A Markov approach is developed to analyze the proposed spectrum sharing policies with generalized bandwidth size in both primary system and secondary system. Performance metrics for SU are developed with respect to blocking probability, interrupted probability, forced termination probability, non-completion probability and waiting time. Numerical examples are presented to explore the impact of key systems parameters like the traffic load on the performance metrics. Comparison results indicate that the buffer is able to significantly reduce the SU blocking probability and non-completion probability with very minor increased forced termination probability. The analytic model has been verified by extensive simulation.
summary: A similar analysis, but with a different channelization structure, where the PU occupied more than one SU channel (contrary to @cite_48 @cite_55 ) was performed in @cite_6 . The authors addressed the cases of (i) connection blocking, and (ii) channel reservation and switching of SU connections to empty channels on PU arrival. This analysis was later extended to the case of finite SU population and packet queuing @cite_39 , and buffering and switching of SU connections preempted by PU arrivals @cite_15 . Again, in all papers listed above the spectrum sensing process was assumed to have no overhead and perfect reliability. Moreover the connection arrangement process for SUs was not considered.