In this paper, we consider the channel allocation problem for throughput maximization in cognitive radio networks with hardware-constrained secondary users. Specifically, we assume that secondary users (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 and its complexity for this non-linear integer optimization problem. Since 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 spectrum opportunities on these channels. 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 to the nonoverlapping channel assignment counterpart. In addition, we design a distributed MAC protocol for access contention resolution and integrate it into the overlapping channel assignment algorithm. We also analyze the saturation throughput and the complexity of the proposed channel assignment algorithms. Moreover, we have presented several potential extensions including greedy channel assignment algorithms under 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. Channel assignment, MAC protocol, spectrum sensing, throughput maximization, cognitive radio. Emerging broadband wireless applications have been demanding unprecedented increase in radio spectrum resources. As a result, we have been facing a serious spectrum shortage problem. However, several recent measurements reveal very low spectrum utilization in most useful frequency bands [1] . Cognitive radio technology is a promising technology that can fundamentally improve the spectrum utilization of licensed frequency bands through secondary spectrum access. However, transmissions from primary users (PUs) should be satisfactorily protected from secondary spectrum access due to their strictly higher access priority. Protection of primary communications can be achieved through interference avoidance or interference control approach (i.e., spectrum overlay or spectrum underlay) [1] . For the interference control approach, transmission powers of SUs should be carefully controlled so that the aggregated interference they create at primary receivers does not severely affect ongoing primary communications [2] . In most practical scenarios where direct coordination between PUs and SUs is not possible and/or if distributed communications strategies are desired, it would be very difficult to maintain these interference constraints. The interference avoidance approach instead protects primary transmissions by requiring SUs to perform spectrum sensing to discover spectrum holes over which they can transmit data [3], [4]. This paper focuses on developing efficient channel assignment algorithms for a cognitive radio network with hardware-constrained secondary nodes using the interference avoidance spectrum sharing approach. In particular, we consider the scenario where each SU can exploit at most one available channel for communications. This can be the case if SUs are equipped with only one radio employing a narrow-band RF front end [5] . In addition, it is assumed that white spaces are so dynamic that it is not affordable for each SU to sense all channels to discover available ones and/or to exchange sensing results with one another. Under this setting, we are interested in determining a set of channels allocated to each SU in advance so that maximum network throughput can be achieved in a distributed manner. To the best of our knowledge, this important problem has not been considered before. The contributions of this paper can be summarized as follows.
Reference REF proposes a distributed MAC protocol with a greedy channel assignment algorithm under the max-min fairness criterion.
Channel Assignment With Access Contention Resolution for Cognitive Radio Networks
Le Thanh Tan; Long Bao Le,"Channel Assignment With Access Contention Resolution for Cognitive Radio Networks,"Vehicular Technology, IEEE Transactions on , vol.61, no.6, pp.2808,2823, July 2012 doi: 10.1109/TVT.2012.2196532
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