Advances in cognitive radio networks: A survey <s> G. Distributed Spectrum Sharing <s> A number of studies have shown the abundance of unused spectrum in the TV bands. This is in stark contrast to the overcrowding of wireless devices in the ISM bands. A recent trend to alleviate this disparity is the design of Cognitive Radios, which constantly sense the spectrum and opportunistically utilize unused frequencies in the TV bands. In this paper, we introduce the concept of a time-spectrum block to model spectrum reservation, and use it to present a theoretical formalization of the spectrum allocation problem in cognitive radio networks. We present a centralized and a distributed protocol for spectrum allocation and show that these protocols are close to optimal in most scenarios. We have implemented the distributed protocol in QualNet and show that our analysis closely matches the simulation results. <s> BIB001 </s> Advances in cognitive radio networks: A survey <s> G. Distributed Spectrum Sharing <s> Cognitive radio is the promising radio technology, which aims to detect and utilize the temporally unused spectrum bands by sensing its radio environment in order to enhance spectrum utilization. However, these objectives bring significant challenges and required functionalities such as spectrum sensing, sharing, management and mobility for the realization of cognitive radio networks (CRN). In particular, efficient spectrum sharing problem in cognitive radio communication is one of the most important problem which must be addressed in order to enhance the overall spectrum utilization in dynamic spectrum access environments. In this paper, we introduce a new BIOlogically-inspired spectrum sharing (BIOSS) algorithm which is based on the adaptive task allocation model in insect colonies. Without need for any coordination among the unlicensed users, BIOSS enables each unlicensed user to distributively determine the appropriate channel(s) over which it can communicate. Performance evaluations clearly reveal that BIOSS achieves efficient dynamic spectrum sharing with high spectrum utilization and without any coordination among the users and hence yielding no spectrum handoff latency overhead due to coordination. <s> BIB002 </s> Advances in cognitive radio networks: A survey <s> G. Distributed Spectrum Sharing <s> Dynamic spectrum access is a promising technique to use spectrum efficiently. Without being restricted to any prefixed spectrum bands, nodes choose operating spectrum on-demand. Such flexibility, however, makes efficient and fair spectrum access in large-scale networks a great challenge. Prior work in this area focused on explicit coordination where nodes communicate with peers to modify local spectrum allocation, and may heavily stress the communication resource. In this paper, we introduce a distributed spectrum management architecture where nodes share spectrum resource fairly by making independent actions following spectrum rules. We present five spectrum rules to regulate node behavior and maximize system fairness and spectrum utilization, and analyze the associated complexity and overhead. We show analytically and experimentally that the proposed rule-based approach achieves similar performance with the explicit coordination approach, while significantly reducing communication cost. <s> BIB003 </s> Advances in cognitive radio networks: A survey <s> G. Distributed Spectrum Sharing <s> This paper investigates a distributed and adaptive approach to manage spectrum usage in dynamic spectrum access networks. While previous works focus on centralized provisioning, we propose a distributed low complexity approach where nodes self-organize into coordination groups and adapt their spectrum assignment to approximate the global optimal assignment. We design a distributed coordination protocol to regulate the coordination format and achieve fast system convergence. The proposed approach achieves similar performance in spectrum assignment compared to that of the conventional centralized approaches, but significantly reduces the number of computations and message exchanges required to adapt to topology changes. As a case study, we investigate the detailed coordination strategy to improve proportional fairness in spectrum assignment, and derive a theoretical lower bound on the minimum spectrum/througput each node can get from coordination. Such bound can be utilized to guide the coordination procedures. We also show that the difference between the proposed approach and the global optimal approach is upper-bounded. Experimental results demonstrate that the proposed approach provides similar performance as the topology-based optimization but with more than 50% of reduction in complexity. <s> BIB004 </s> Advances in cognitive radio networks: A survey <s> G. Distributed Spectrum Sharing <s> In this paper, we investigate the problem of multiuser resource management in multihop cognitive radio networks for delay-sensitive applications. Since tolerable delay does not allow propagating global information back and forth throughout the multihop network to a centralized decision maker, the source nodes and relays need to adapt their actions (transmission frequency channel and route selections) in a distributed manner, based on local network information. We propose a distributed resource-management algorithm that allows network nodes to exchange information and that explicitly considers the delays and cost of exchanging the network information over multihop cognitive radio networks. In this paper, the term ldquocognitiverdquo refers to both the capability of the network nodes to achieve large spectral efficiencies by dynamically exploiting available frequency channels and their ability to learn the ldquoenvironmentrdquo (the actions of interfering nodes) based on the designed information exchange. Note that the node competition is due to the mutual interference of neighboring nodes using the same frequency channel. Based on this, we adopt a multiagent-learning approach, i.e., adaptive fictitious play, which uses the available interference information. We also discuss the tradeoff between the cost of the required information exchange and the learning efficiency. The results show that our distributed resource-management approach improves the peak signal-to-noise ratio (PSNR) of multiple video streams by more than 3 dB, as opposed to the state-of-the-art dynamic frequency channel/route selection approaches without learning capability, when the network resources are limited. <s> BIB005
In centralized spectrum allocation, a lot of information needs to be exchanged among the central controller and network users to coordinate their spectrum usage, and this results in a large amount of signaling overhead. Therefore, distributed spectrum sharing is preferred where users can make their decision on how to use the spectrum solely based on local information. A distributed spectrum management scheme is proposed in BIB003 , where nodes take independent actions and share spectrum resource fairly. An adaptive approach to manage spectrum usage in dynamic spectrum access networks is investigated in BIB004 . Considering the frequency agility and adaptive bandwidth, the concept of time-spectrum block is introduced in BIB001 , and a distributed protocol is developed to solve the spectrum allocation problem which enables each node to dynamically choose the best time-spectrum block based only on local information. Based on the adaptive task allocation model in insect colonies, a biologically-inspired spectrum sharing algorithm is introduced in BIB002 . The proposed algorithm enables secondary users to distributively determine the appropriate channels to use with no spectrum handoff latency due to coordination, and achieves efficient spectrum sharing. A distributed resource-management algorithm that allows network nodes to exchange information and learn the actions of interfering nodes using multi-agent learning approach is proposed in BIB005 .