In this paper, we consider the channel assignment problem for cognitive radio networks with hardware-constrained secondary users (SUs). In particular, we assume that SUs exploit spectrum holes on a set of channels where each SU can use at most one available channel for communication. We present the optimal brute-force search algorithm to solve the corresponding nonlinear integer optimization problem and analyze its complexity. Because the optimal solution has exponential complexity with the numbers of channels and SUs, we develop two low-complexity channel assignment algorithms that can efficiently utilize the spectrum holes. In the first algorithm, SUs are assigned distinct sets of channels. We show that this algorithm achieves the maximum throughput limit if the number of channels is sufficiently large. In addition, we propose an overlapping channel assignment algorithm that can improve the throughput performance compared with its nonoverlapping channel assignment counterpart. Moreover, we design a distributed medium access control (MAC) protocol for access contention resolution and integrate it into the overlapping channel assignment algorithm. We then analyze the saturation throughput and the complexity of the proposed channel assignment algorithms. We also present several potential extensions, including the development of greedy channel assignment algorithms under the max-min fairness criterion and throughput analysis, considering sensing errors. Finally, numerical results are presented to validate the developed theoretical results and illustrate the performance gains due to the proposed channel assignment algorithms.
A multi-channel parallel transmission protocol is proposed for the medium access control in cognitive radio networks (CRNs). This protocol contains two key elements: multi-channel assignment and multi-channel contention. For an incoming flow-based connection request, the minimum number of parallel channels are assigned to satisfy the rate and interference mask constraints. For the contention of the assigned channels, our protocol provides an extension of the single-channel RTS- CTS-DATA-ACK handshaking of the IEEE 802.11 scheme. The proposed MAC coherently integrates optimization results into a practical implementation. Through numerical examples, we verify that our protocol provides lower connection blocking probability and higher system throughput for CRNs than its single-channel counterpart. As the radio spectrum usage paradigm shifting from the traditional command and control allocation scheme to the open spectrum allocation scheme, wireless ad-hoc networks meet new opportunities and challenges. The open spectrum allocation scheme has potential to provide those networks more capacity, and make them more flexible and reliable. However, the freedom brought by the new spectrum allocation scheme introduces spectrum management and network coordination challenges. Moreover, wireless ad-hoc networks usually rely on a common control channel for operation. Such a control channel may, however, not always available in an open spectrum allocation scheme due to the interference and the need for coexistence with primary users of the spectrum. Instead, common channels most likely exist in a local area.In this paper, we propose a cluster-based framework to form a wireless mesh network in the context of open spectrum sharing. Clusters are constructed by neighbor nodes sharing local common channels, and the network is formed by interconnecting the clusters gradually. We identify issues in such a network and provide mechanisms for neighbor discovery, cluster formation, network formation, and network topology management. The unique feature of this network is its ability to intelligently adapt to the network and radio environment change. Cognitive radio (CR) is the key enabling technology for an efficient dynamic spectrum access. It aims at exploiting an underutilized licensed spectrum by enabling opportunistic communications for unlicensed users. In this work, we first develop a distributed cognitive radio MAC (COMAC) protocol that enables unlicensed users to dynamically utilize the spectrum while limiting the interference on primary (PR) users. The main novelty in COMAC lies in not assuming a predefined CR-to-PR power mask and not requiring active coordination with PR users. COMAC provides a statistical performance guarantee for PR users by limiting the fraction of the time during which the PR users' reception is negatively affected by CR transmissions. To provide such a guarantee, we develop probabilistic models for the PR-to-PR and the PR-to-CR interference under a Rayleigh fading channel model. From these models, we derive closed-form expressions for the mean and variance of interference. Empirical results show that the distribution of the interference is approximately lognormal. Based on the developed interference models, we derive a closed-form expression for the maximum allowable power for a CR transmission. We extend the min-hop routing to exploit the available channel information for improving the perceived throughput. Our simulation results indicate that COMAC satisfies its target soft guarantees under different traffic loads and arbitrary user deployment scenarios. Results also show that exploiting the available channel information for the routing decisions can improve the end-to-end throughput of the CR network (CRN).