Receiver-Based Channel Allocation for Wireless Cognitive Radio Mesh Networks

Empowered by the cognitive radio technology, and motivated by the sporadic channel utilization, both spatially and temporally, dynamic spectrum access networks (also referred to as cognitive radio networks and next generation wireless networks) have emerged as a solution to improve spectrum utilization and provide more flexibility to wireless communication. A cognitive radio network is composed of wireless users, referred to as secondary users, which are allowed to use a given licensed spectrum band as long as there are no primary, licensed, users occupying this band in their vicinity. This restricted spectrum access strategy leads to heterogeneity in channel availability among secondary users. Heterogeneity in channel availability forms a significant source of performance degradation for cognitive radio networks, and poses a great challenge on protocol design. In this dissertation, we propose spectrum allocation algorithms that take this heterogeneity property and its effect on the network performance into consideration. The spectrum allocation solutions proposed in this dissertation address three major objectives in cognitive radio mesh networks. The first objective is maximizing the network coverage, in terms of the total number of served clients, and at the same time simplifying the communication coordination function. To address this objective, we proposed a received based channel allocation strategy that alleviates the need for a common control channel, thus simplifying the coordination function, and at the same time maximizes the number of clients served with link reliability guarantees. We show the superiority of the proposed allocation strategy over other existing strategies. The second objective is improving the multicast throughput to compensate for the performance degradation caused by the heterogeneity in channel availability. We proposed a

Cognitive Radio (CR) technology constitutes a promising approach to increase the capacity of Wireless Mesh Networks (WMNs). Using this technology, Mesh Routers (MRs) and the attached Mesh Clients (MCs) are allowed to opportunis- tically transmit on the licensed band, but under the constraint not to interfere with the Primary Users (PUs) of the spectrum. Thus, the effective deployment of CR- WMNs require that each MR must be able to: sense the current spectrum, select an available PU-free channel and perform the spectrum handoff to a new channel in case of PU arrival on the current one. How to coordinate these actions in the optimal way which maximizes the performance of the CR-WMNs while minimizing the interference to the PUs constitutes an open research issue in CR systems. In this paper, we propose an adaptive spectrum scheduling and allocation scheme which allows a MR to identify the best schedule of (i) when to sense the current channel, (ii) when to transmit, (iii) when to perform a spectrum handoff. Due the large number of parameters involved, we propose Reinforcement Learning (RL) techniques to allow a MR to learn by itself the optimal balance between spectrum sensing-exploitation- exploration actions based on network feedbacks coming from the MCs. We perform extensive simulations which confirm the adaptivity and efficiency of our approach in terms of increased throughput when compared with non-learning based schemes for CR-WMNs.

Cognitive radio (CR) networks are expected to offer a huge bandwidth to wireless users through dynamic spectrum access techniques. To realize this new network paradigm, effective distributed coordination schemes to exchange control information without assuming the availability of a prespecified common control channel (CCC) are needed. In this paper, we propose a distributed group-based spectrum-aware coordination scheme for carrier-sense multiple access with collision avoidance (CSMA/CA)-based CR networks, which is called virtual clustering distributed coordination (VCDC). By using a CSMA/CA access mechanism, VCDC allows neighboring CR users with a similar view to spectrum opportunities to asynchronously organize themselves into virtual clusters and coordinate their communications using locally available CCCs. VCDC differs from previous cluster-based schemes in that it exploits the discrete orthogonal frequency-division multiplexing (D-OFDM) technology to reduce neighbor-discovery time and facilitate intercluster communication and broadcasting. Three variants of the VCDC scheme are proposed, which are one-hop, two-hop, and constrained VCDC. These variants provide different cluster size based on the number of adopted local CCCs. We compare the performance of the VCDC scheme with existing clustering schemes. Simulation results show that VCDC constructs fewer larger size clusters with an appropriate number of common idle channels and introduces a lower percentage of clusters with no shared idle channels. Thus, VCDC performs better without imposing synchronization.

We propose a coordinated non-sensing medium access control (MAC) protocol in dynamic spectrum access networks namely distributed coordinated dynamic spectrum reservation (DCDSR) protocol which is not based on the cognitive radio technology. All primary users (PUs) and secondary users (SUs) have two transceivers operating in common control channel and licensed data channels to access control and data packets in the corresponding control and data frames, respectively. PUs will inform SUs which channels will be used in next data frame and then SUs reserve unused channels by contending with each other during contention interval (CI) in control frame. The available channels which can be reserved by SUs will depend on the channel usage of PUs and further affect the throughput of SUs. Whenever SU successfully reserve channel in CI, they will start access reserved channel in next data frame after the end of CI. This will cause the wasted idle time for those SUs which have successfully reserved channel whenever the CI doesn't finish. SU which couldn't successfully reserve channel in current control frame should try to reserve again in next control frame. Thus, the duration of CI will affect the delay and wasted idle time of SUs. We analyze and simulate the performance of throughput, delay and wasted idle time in DCDSR. The analytical and simulation results show that the proposed DCDSR performs very well.

Wireless Mesh Network (WMN) is a multi hop low cost, with easy maintenance robust network providing reliable service coverage. WMNs consist of mesh routers and mesh clients. In this architecture, while static mesh routers form the wireless backbone, mesh clients access the network through mesh routers as well as directly meshing with each other. Different from traditional wireless networks, WMN is dynamically self-organized and self-configured. In other words, the nodes in the mesh network automatically establish and maintain network connectivity. Over the years researchers have worked, to reduce the redundancy in broadcasting packet in the mesh network in the wireless domain for providing reliable service coverage, the source node deserves to broadcast or flood the control packets. The redundant control packet consumes the bandwidth of the wireless medium and significantly reduces the average throughput and consequently reduces the overall system performance. In this paper I study the optimization problem in Wireless Mesh Networks. We have proposed a novel approach to reduce the broadcast redundant packet in the wireless mesh network. Also we have shown, a novel procedure to forward the control packet to the destination nodes and efficiently minimize the transmitted control packet in the wireless mesh cloud , that covers the domain.

Cognitive radio (CR) technology has been attracted as a solution for the frequency scarcity problem in the wireless mesh network which operates on multiple frequency bands (or channels). In this paper, we consider the channel assignment and routing in CR-based wireless mesh networks (CRWMNs). In the CRWMN, CR nodes access the channels without disturbing primary users (PUs) which have a privilege to access the channels. When a PU is activated on one of the operating channels of the CRWMN, the network should update the channel assignment and routing to protect the transmission of the PU. This update, called joint channel assignment and routing update (JCAR-update), causes large signaling overhead in the CRWMN. To reduce such signaling overhead, we propose a two-step JCAR-update scheme. In the first step, each CR node tries to perform a simple recovery algorithm in a distributed way. The recovery algorithm is to reassign channels to affected links without exchanging control information. In the second step, only if the recovery fails, the CRWMN re-optimizes the channel assignment and routing. Simulation results show that the proposed scheme reduces the signaling overhead and supports stable operation in CRWMNs.

In this paper, we propose a new distributed approach for the electrical substation monitoring in suburban environment using the cognitive radio (CR) technology. For instance, suburban areas are characterized by the scarcity of the free-accessed wireless bands due to their proximity to inhabitants' zones and the abundance of the usually underutilized spectrum resources provided by the operators. Thus, our focus is to fully benefit from the cognitive radio sensor network (CRSN) technology to provide efficient data aggregation and reporting processes in substations upon unexpected events' detection. Our approach, called Distributed Event-driven data Aggregation and constrained multipath Routing (DEAR), will completely emancipate from the common control channel (CCC) limitations, generally used for the channel assignment in cognitive networks. DEAR uses the graph coloring paradigm for the licensed spectrum allocation during the data aggregation and reporting phases and a constrained multipath ”Beam” routing to prevent packet loss and failures in the harsh substation environment. Performance evaluation reveals that DEAR ensures a rapid data transmission and an efficient channel assignment in CRSNs.

In the recent years Cognitive Radio (CR) technology imposed itself like a very good solution to the increasing spectrum utilization. This technology proposes the development of a new radio type - a cognitive radio - endowed with intelligence that shall sense, share, and use the spectrum opportunities (SOP) of the preexisting wireless networks, that is the channels that are not used by the licensed users. A new routing algorithm for CR networks (CRN): IPSAG - IP Spectrum Aware Geographic based Routing Protocol is presented in the paper. As suggested by the name, the IP hop-by-hop, the geographic, and the spectrum aware routing concepts were used together in the protocol's design. The dynamism and flexibility, characteristic to both CR and IP networks, made us compare the CR concept with the IP concept (a wireless versus wired flexible environment comparison); thus we assumed the IP routing approach for CRN. The proposed strategy is based on hop-by-hop routing, local decisions being taken by nodes according to both local information (CR node's neighborhood) and global information (the entire topology of CRN), channels availability, and destination location.

Wireless Mesh Networks (WMNs) have recently emerged as a technology for next-generation wireless networking. WMNs partially replace wired backbone networks, and it is therefore reasonable to plan carefully radio resource assignment to provide quality guarantees to traffic flows. Directional transmissions allow to reduce radio interference, thus exploiting spatial reuse. Therefore, as a main contribution, in this paper we study the joint routing and scheduling optimization problem in Wireless Mesh Networks where nodes are equipped with directional antennas. To this aim, we assume a Spatial reuse Time Division Multiple Access (STDMA) scheme, a dynamic power control able to vary the emitted power slot-by-slot, and a rate adaptation mechanism that sets transmission rates according to the Signal- to-Interference-and-Noise Ratio (SINR). We provide column generation-based heuristic approaches for the proposed models in a set of realistic-size instances and discuss the impact of different parameters on the network performance. The results show that our schemes increase considerably the total traffic accepted by the network, providing bounds to the achievable performance.

One of the ways to harness the radio bands that are not used by their primary owners, is to allow opportunistic use of the bands to be used by secondary users such that they do not interfere with the primary users. Most often, multiple secondary users contend to acquire the bands that are available. Proper scheduling techniques can resolve such contentions. However, all scheduling techniques have their own pros and cons. In this paper, we propose scheduling algorithms for dynamic spectrum access (DSA) networks that allocate channels by exploiting favorable instantaneous channel conditions of secondary users and the transmission activities of primary users. We propose two scheduling algorithms- the first one focuses on maximizing the throughput and the second one focuses on social welfare. Scheduling is performed at the beginning of each super-frame where appropriate slots(s) are assigned to secondary users. In order to better utilize the channels, multiple secondary users are allocated the same channel in the same time slot as long as there is no interference between them. However, finding such conflict-free independent set of secondary users is a NP-complete problem. We use the signal to interference and noise ratio (SINR) to find the independent sets for throughput maximization, while we use the allocation history for the achieving fairness. Using simulation, we show the performances of the proposed algorithms in terms of throughput, number of slots allocated, and fairness achieved among the users.

This paper presents a Bayesian potential game to model distributed joint power and channel allocation for cognitive radios with incomplete information. We propose a cooperative approach where secondary users (SUs) devote part of their transmission power in licensed channels to relaying primary users' (PUs) messages. In addition, we consider incomplete information in the decision making process, so as to avoid the need for a common control channel (CCC), where users share information. This hypothesis improves the robustness and feasibility of the cognitive radio network supported by the proposed approach. Simulation results show that cooperation benefits both PUs and SUs and that the lack of complete information in the decision process slightly reduces performances in terms of signal to interference and noise ratio (SINR) and outage probability.

Cognitive radio technologies enable users to opportunistically access unused licensed spectrum and are viewed as a promising way to deal with the current spectrum crisis. Over the last 15 years, cognitive radio technologies have been extensively studied from algorithmic design to practical implementation. One pressing and fundamental problem is how to integrate cognitive radios into current wireless networks to enhance network capacity and improve users’ experience. Unfortunately, existing solutions to cognitive radio networks (CRNs) suffer from many practical design issues. To foster further research activities in this direction, we attempt to provide a tutorial for CRN architecture design. Noticing that an effective architecture for CRNs is still lacking, in this tutorial, we systematically summarize the principles for CRN architecture design and present a novel flexible network architecture, termed cognitive capacity harvesting network (CCHN), to elaborate on how a CRN architecture can be designed. Unlike existing architectures, we introduce a new network entity, called secondary service provider, and deploy cognitive radio capability enabled routers, called cognitive radio routers, in order to effectively and efficiently manage resource harvesting and mobile traffic while enabling users without cognitive radios to access and enjoy CCHN services. Our analysis shows that our CCHN aligns well to industrial standardization activities and hence provides a viable approach to implementing future CRNs. We hope that our proposed design approach opens a new venue to future CRN research.

The cognitive radio technology aims to increase the spectrum utilization by accessing opportunistically the unused spectrum bands. Multicarrier communications are considered to be used in cognitive radio systems. In cognitive radio systems, the power allocation should be carried out within the cognitive radio network so that no excessive interference is caused to the primary user. In this paper, an iterative power allocation algorithm is proposed to maximize the downlink capacity of the cognitive radio system under both the total power budget and interference introduced to the primary user constraints. Moreover, two complexity reduced algorithms are presented. The problem of channel allocation in multiuser cognitive radio networks is discussed. Finally, the performance of the proposed algorithms is investigated using computer simulations.KeywordsCognitive RadioPower AllocationOrthogonal Frequency Division Multiplex SystemCognitive Radio SystemSubcarrier AllocationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

A multi-radio Wireless Mesh Network (WMN) is a multi-hop network that consists of mesh routers and mesh clients, where mesh routers are equipped with multiple radio interfaces and form the backbone of the mesh network. To provide backbone support, it is necessary to reduce interference and balance load in Wireless Mesh Networks (WMNs). We propose load-aware routing metric (LARM), which captures the difference in transmission rates, packet loss ratio, intra/inter-flow interference and traffic load in multi-radio mesh networks. The LARM metric helps finding paths that are better in terms of balancing load and reducing the inter-flow and intra-flow interference in multi-radio networks. Simulation results show that LARM metric significantly outperforms several existing routing metrics in multi-radio wireless mesh networks.

Cognitive Radio (CR) exploits underutilized licensed spectrums to improve its bandwidth availability. Using CR technology, a node is able to adapt its transmission and reception radio parameters including channel frequency dynamically according to local spectrum availability. For channel access between wireless nodes, a cognitive Medium Access Control (MAC) protocol is necessary to coordinate the CRs. Multi-channel MAC protocol extensions have been proposed in IEEE802.11 to enable a node to operate in multiple channels in order to improve network-wide throughput. These multi-channel MAC protocols have several functions that can be leveraged by cognitive MAC protocols due to their similarities in certain aspects, though the CR has an additional requirement to cope with the existence of licensed users that have higher authority over the channels. Current research in cognitive MAC protocols assumes the availability of a common control channel at all times, which is an approach in the multi-channel MAC protocols. This approach has certain hardware requirements that may not be readily available at CR nodes. Hence, other approached may be necessary. In this paper, various types of multi-channel MAC protocols are reviewed, followed by discussion of their merits and demerits in multi-channel environments. The purpose is to show the additional functionalities and challenges that each multi-channel MAC protocol has to offer and address in order to operate in multihop CR networks. By providing discussion on possible technology leverage from multi-channel to cognitive MAC protocols, we aim to establish a foundation for further research and discussion.