Spectrum allocation and medium access in cognitive radio wireless 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

In this paper we have studied the subcarrier and optimal power allocation strategy for OFDM-based cognitive radio (CR) networks. Firstly, in order to protect the primary user communication from the interference of the cognitive user transmissions in fading wireless channels, we design an opportunistic power control scheme to maximize the cognitive user capacity without degrading primary user's QoS. The mathematical optimization problem is formulated as maximizing the capacity of the secondary users under the interference constraint at the primary receiver and the Lagrange method is applied to obtain the optimal solution. Secondly, in order to limit the outage probability within primary user's tolerable range we analyze the outage probability of the primary user with respect to the interference power of the secondary user for imperfect CSI. Finally, in order to get the better tradeoff between fairness and system capacity in cognitive radio networks, we proposed an optimal algorithm of jointing subcarrier and power allocation scheme among multiple secondary users in OFDM-based cognitive radio networks. Simulation results demonstrate that our scheme can improve the capacity performance and efficiently guarantee the fairness of secondary users.

In this paper, we exploit a novel setting for Cognitive Radio (CR) networks to enable multiple operators to involve secondary users (SUs) as cooperative relays for their primary users. In return, SUs get an opportunity to access spare channels for their own data transmission. Initially, we assume that the CR network supports payment transfer. Then, we formulate the system as a transferable utility coalitional game. We show that there is an operating point that maximizes the sum utility over all operators and SUs while providing each player a share such that no subset of operators and SUs has an incentive to break away from the grand coalition. Such operating points exist when the solution set of the game, the core, is nonempty. Subsequently, we examine an interesting scenario where there is no payment mechanism in the network. This scenario can be investigated by using a nontransferable utility coalitional game model. We show that there exists a joint action to make the core nonempty. A general method with exponential computational complexity to get such a joint action is discussed. Then, we relate the core of this game to a competitive equilibrium of an exchange economy setting under special situations. As a result, several available efficient centralized or distributed algorithms in economics can be employed to compute a member in the core. In a nutshell, this paper constitutes the design of new coalition based dynamics that could be used in future CR networks.

With the rapid development of wireless services and applications, the currently radio spectrum is becoming more crowded. How to accommodate more wireless services and applications within the limited radio spectrum becomes a big challenge faced by modern society. Cognitive radio (CR) is proposed as a promising technology to tackle this challenge by introducing secondary users (SUs) to opportunistically or concurrently access the spectrum allocated to primary users (PUs). Currently, there are two prevalent CR models: the spectrum sharing model and the opportunistic spectrum access model. In the spectrum sharing model, the SUs are allowed to coexist with the PUs as long as the interferences from SUs do not degrade the quality of service (QoS) of PUs to an unacceptable level. In the opportunistic spectrum access model, SUs are allowed to access the spectrum only if the PUs are detected to be inactive. These two models known as underlay and overlay schemes, respectively. This thesis studies a number of topics in CR networks under the framework of these two schemes. First, studied cognitive radio transmissions under QoS delay constraints. Initially, we focused on the concept: effective capacity for cognitive radio channels in order to identify the performance in the presence of QoS constraints. Both underlay and overlay schemes are studied taking into consideration the activity of primary users, and assuming the general case of channel fading as Gamma distribution. For this setting, we further proposed a selection criterion by which the cognitive radio network can choose the adequate mode of operation. Then, we studied the cognitive radio transmissions focusing on Rayleigh fading channel and assumed that no prior channel knowledge is available at the transmitter and the receiver. We investigated the performance of pilot-assisted transmission strategies. In particular, we analyzed the channel estimation using minimum mean-square-error (MMSE) estimation, and analyzed efficient resource allocation strategies. In both cases, power allocations and effective capacity optimization were obtained. Effective capacity and interference constraint were analyzed in both single-band and multi-band spectrum sensing settings. Finally, we studied optimal access probabilities for cognitive radio network using Markov model to achieve maximum throughput for both CR schemes.

Joint spectrum allocation and scheduling for fair spectrum sharing in cognitive radio wireless networks

This paper considers a cognitive radio (CR) network comprising one cognitive base station (CBS) and a number of secondary users (SUs) that shares a set of channels with a primary network. Both uplink and downlink scenarios are considered in the CR network. The objective is to maximize the throughput of the CR network while protecting the primary transmission and maintaining fairness among the SUs. To fairly allocating resources among the SUs, minimum/maximum number of channels constraint of the SU is introduced to flexibly distribute available channels between the SUs. For both uplink and downlink scenarios, we propose a joint channel allocation and power control scheme. Additionally, a low-complexity two-phase channel allocation and power control scheme is also proposed in the downlink scenario. Simulation results are obtained to validate the performance of the proposed schemes. It is shown that the proposed schemes offer flexibility and controllability in fairly allocating channels to the SUs and yet achieve high throughput. Furthermore, it is shown that the performance gap between the joint scheme and the two-phase scheme is negligible.

In this paper, we investigate the problem of spectrum allocation in Cognitive Radio Networks (CRNs) where a primary user (PU) leases its idle spectrums to a number of secondary users (SUs) who may have different willing to pay for these spectrums. For the PU, its main objective is to gain profit from selling the idle spectrums, and from the perspective of the Sus, they aim to maximize their utility from using spectrums. We model the interaction between the PU and SUs as a two-stage Stackelberg game, where the PU sets the prices for its spectrum in the first stage, and SUs make their spectrum demands decisions in the second stage. We use the backward induction method to solve this game. The numerical results show that the proposed solution method can increase revenue of the PU compared with the uniform pricing scheme.

In this paper, we consider the problem of improving the performances of large Cognitive Radio Wireless Networks (CRWN). The lack of network infrastructure and heterogeneous spectrum availability in cognitive radio wireless networks require the self-organization of secondary users (SUs) for efficient spectrum assignment. The cluster structure can be an adequate solution in both guaranteeing system performance and reducing communication overhead in CRWN. The approach considered in this paper relays on the use of a coalitional game in every cluster to preserve energy loss in the sensing phase and to reduce the interference with primary users (PUs) and between SUs. First, we study the coalitional formation process in partition form with non-transferable utility (NTU). In order to reduce the coalition formation cost, a cluster scheme is considered. Then, we use a strategic learning algorithm to learn the Nash equilibrium. At the end, simulation results demonstrate the preference of our CRWN compared to standard wireless cognitive network.

A cognitive radio (CR) network refers to a secondary network operating in a frequency band originally licensed/allocated to a primary network consisting of one or multiple primary users (PUs). A fundamental challenge for realizing such a system is to ensure the quality of service (QoS) of the PUs as well as to maximize the throughput or ensure the QoS, such as signal-to-interference-plus-noise ratios (SINRs), of the secondary users (SUs). In this paper, we study single-input multiple output multiple access channels (SIMO-MAC) for the CR network. Subject to interference constraints for the PUs as well as peak power constraints for the SUs, two optimization problems involving a joint beamforming and power allocation for the CR network are considered: the sum-rate maximization problem and the SINR balancing problem. For the sum-rate maximization problem, zero-forcing based decision feedback equalizers are used to decouple the SIMO-MAC, and a capped multi-level (CML) water-filling algorithm is proposed to maximize the achievable sum-rate of the SUs for the single PU case. When multiple PUs exist, a recursive decoupled power allocation algorithm is proposed to derive the optimal power allocation solution. For the SINR balancing problem, it is shown that, using linear minimum mean-square-error receivers, each of the interference constraints and peak power constraints can be completely decoupled, and thus the multi-constraint optimization problem can be solved through multiple single-constraint sub-problems. Theoretical analysis for the proposed algorithms is presented, together with numerical simulations which compare the performances of different power allocation schemes.

This paper proposes a spatial time-division multiple access (STDMA) based scheme (STBS) to enhance the system throughput in cognitive radio wireless networks. Especially, the proposed scheme is suitable for the situation when the available number of channels is far less than the number of secondary users (SUs). The system design includes: 1) a novel criterion based on SINR constraint (SC) to determine the feasibility of spatial reuse of spectrum; 2) a heuristic spectrum allocation and scheduling (HSAS) algorithm. Simulation results show that in comparison with the STBS based on Interference range (IR) criterion proposed in [5], the proposed scheme can improve the system throughput as much as 100% when the number of channels is 1/5 of the number of users as well as guarantee a low outage ratio of system blow 2% in various scenarios.

In this paper, we study the problem of jointing power and rate optimization in multi-channel Heterogeneous Cognitive Radio Networks (H-CRNs), where the Leader-Follower relationship between Primary Users (PUs) in macrocells and Secondary Users (SUs) in femtocells is modeled as a Stackelberg game. We formulate the problem of power allocation in primary networks as a Non-Cooperative Game, while formulating the jointing power and rate optimization in cognitive networks as a Market Competition Equilibrium problem. Furthermore, we propose a Primary networks and Cognitive networks Joint Resource Allocation (PCJRA) algorithm to maximize the utilities of SUs subject to the maximum rate requirements for PUs. Theoretical analysis and simulation results demonstrate both the feasibility of the multi-channel H-CRNs model and the effectiveness of the proposed PCJRA algorithm.

The optimal admission control for secondary users (SUs) using blockchain technology in a cognitive radio (CR) network is investigated in this paper. When an SU comes to the system, it will decide to either enter the system, or give up its service and then leave the system based on the current number of PU and SU users in the network. SUs are linked as a block in the waiting area to access the spectrum in an opportunistic way without interfering the operations of PUs. When a PU arrives, if the band is occupied by SU(s), the SU service on the band is interrupted and SU(s) is then placed back to the waiting queue. Admitting an SU would bring a reward to the system provider but holding an SU in the system would also incur an expense to the provider. We concentrate on the optimization problem of when to admit or reject an arriving SU in order to achieve the maximum total discounted expected reward for any initial state. By establishing a discounted Continuous Time Markov Decision Process (CTMDP) model, we verify that the optimal policies for admitting SUs are state-related control limit policies. An extensive numerical analysis is implemented to show how to determine the value of optimal threshold and of the corresponding maximum objective function. Especially, a simulation by using the idea of the neural network and machine learning is implemented to show how to determine the optimal threshold value for any new input parameters through learning process for a given input parameters. The idea and the corresponding result of this paper can be applied in designing optimal cognitive radio networks.

Cognitive radio has developed as a novelapproach that enables efficient use of unexploited or underutilized parts of frequency bands. Wireless cognitive radio networks aim to speculativelyfeat the empty or underutilized parts of the spectrum by listening to the frequency bands of their secondary users with various sensing techniques. For this purpose, the process of switching from a frequency channel used by secondary users for various reasons to another free channel is defined as spectrum allocation. At the beginning of the cases where the spectrum allocation takes place, the frequency channels allocated to secondary users are put back into the service of primary users. Severaltechniques are utilized for the spectrum allocation process decided by the access points. Artificial intelligence techniques are used to make the decision to realize the spectrum allocation transaction. In this paper, we present a fuzzy logic based spectrum allocation technique and thus ensure better management. The simulation results shows the performance in terms of received signal strength and signal to noise power.

In this paper, a novel spectrum allocation approach for cognitive radio networks (CRNs) is proposed. Based on a measure of inference performance as well as on a measure of quality-of-service, the association between secondary users (SUs) in the network and frequency bands licensed to primary users (PUs) is investigated. The problem is formulated as a matching game between SUs and PUs. In this game, SUs employ hypothesis testing to detect PUs' signals and, eventually, rank them based on the logarithm of the a posteriori probability ratio. A valuation that captures the ranking metric and rate over the PU-owned frequency bands is proposed to PUs in the form of credit or rewards by SUs. Using this proposal, a PU evaluates a utility function that it uses to build its association preferences. A distributed algorithm that allows both SUs and PUs to interact and self-organize into a stable and optimal matching is presented. Simulation results show that the proposed algorithm can improve: i) the sum of SUs' rates by up to 20% and 60% relative to the deferred acceptance algorithm and random channel allocation approach respectively, and ii) the sum of PUs' payoffs by up to 25% compared to the deferred acceptance algorithm. The results also show an improved convergence time.

Opportunistic spectrum access in cognitive radio networks is regarded as solution to spectrum scarcity caused by the static allocation of the frequency spectrum. Unlicensed secondary users (SUs) access the spectrum opportunities which are licensed not licensed to them opportunistically without creating harmful interference to the licensed primary users (PUs). In typical wireless communications, to negotiate and establish a link between transmitter and receiver, common control channel is used. However, attackers can identify the common channel and jam it or overhear and misuse the information. In this paper, we present rendezvous processes for dynamic spectrum access in cognitive wireless networks where transmitter and receiver pair meets in a common channel in an ad hoc manner and establish a link for their communications. Rendezvous processes for dynamic spectrum access provides robust link that prevents any security attacks such as jamming, denial-of-service attack, etc. This paper provides comparison of different rendezvous processes and their applicability in cognitive wireless ad hoc networks.