Performance Analysis of a Cognitive Network with Dynamic Spectrum Assignment to Secondary Users

Spectrum sensing is an essential operation in cognitive radio networks. In this paper, we consider a dynamic spectrum sensing system consisting of both non-cooperative mobile cognitive radio(CR) secondary users and mobile non-cognitive radio primary users. Key performance metrics such as detection capability and sensing capacity are evaluated. Two mobility models are adopted for both secondary and primary users. The relative distance distribution associating the independent mobile users is analyzed and given in both 1- and 2-dimensions. Expressions for both performance metrics are derived, and simulations are performed to validate the theoretical analyses.

Turning foes to allies in cognitive radio networks

We investigate opportunistic cooperation between secondary (unlicensed) users and primary (licensed) users in cognitive radio networks. We consider two models for such cooperation. In the first model, called the Cooperative Relay Model, a secondary user cannot transmit its own data concurrently with a primary user. However, it can employ cooperative relaying in order to improve the effective transmission rate of the primary user. In the second model, called the Interference Model, a secondary user is allowed to transmit its data concurrently with a primary user. However, the secondary user can “cooperate” by deferring its transmissions when the primary user is busy. In both models, the secondary users must make intelligent cooperation decisions as they seek to maximize their own throughput subject to average power constraints. The decision options are different during idle and busy periods of the primary user, and the decisions in turn influence the durations of these periods according to a controllable infinite state Markov chain. Such problems can be formulated as constrained Markov decision problems, and conventional solution techniques require either extensive knowledge of the system dynamics or learning based approaches that suffer from large convergence times. However, using a generalized Lyapunov optimization technique, we design a novel greedy and online control algorithm that overcomes these challenges. Remarkably, this algorithm does not require any knowledge of the network arrival rates and is provably optimal.

Motivated by the low utilization of the licensed spectrum across many frequency bands, sensing-based oppor- tunistic spectrum access has recently emerged as an alternative to the outdated exclusive spectrum access policy. Under this new paradigm, a secondary (unlicensed) user monitors a primary (licensed) frequency band for a given and opportunistically transmits if it does not detect any ongoing licensed operations. Evidently, selection of the parameters involves balanc- ing a tradeoff between the speed and the quality with which the secondary user senses the licensed band. With the average throughput as the performance criterion, we obtain the parameters so as to optimize the performance of the secondary user while providing the primary user with its desired level of interference protection. I. INTRODUCTION As evidenced by recent measurements, many frequency bands across the licensed spectrum are significantly under- utilized (1), (2). This finding suggests that the spectrum scarcity, as perceived today, is largely due to the inefficient fixed frequency allocations rather than the physical shortage of the spectrum and has led the regulatory bodies to consider the opportunistic access to the temporally/spatially unused licensed bands (a.k.a. the white spaces) as a means to improve the efficiency of spectrum usage. In the absence of cooperation or signalling between the primary licensee and the secondary users, spectrum availability for the opportunistic access may be determined by direct spectrum where the secondary user monitors a licensed band for a given sensing time and opportunistically transmits if it does not detect any ongoing licensed operations. This approach is particularly appealing due to its low deployment cost and its compatibility with legacy primary users and is being considered for inclusion in the upcoming IEEE 802.22 standard for opportunistic access to the TV spectrum (3). Due to their ability to autonomously detect and to react to the changes in the spectrum usage, secondary users equipped with the spectrum capability may be considered as a primitive form of the cognitive radio (4). Design of any scheme involves balancing a tradeoff between the quality and the speed of through an appropriate selection of the time. As we shall illustrate, in the context of spectrum sensing, may be fine- tuned to enhance the secondary users' perceived quality-of- service (QoS) as long as the regulatory constraint for the protection of the primary users against harmful interference is satisfied. In particular, we will obtain the optimum times at different stages of the spectrum to maximize the average throughput of the secondary user. In this paper, simple energy detection (a.k.a. radiometry) (5) is chosen as the underlying detection scheme. In general, when some information about the structure of the primary signal is available, ad hoc feature-detectors offer a better performance (6). We note, however, that the methodology employed in this paper may be applied to optimize different spectrum sensors once the quality is characterized in terms of the time. The remainder of this paper is organized as follows. The regulatory constraints on spectrum are described in the following section. Section 3 provides an overview of the energy-based spectrum sensing. The optimum times for different stages of the spectrum are derived in Section 4. Finally, this paper is concluded in Section 5.

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.

The cooperation among the secondary users or among the secondary users and the primary users have proven to bring many benefits to both primary and secondary users in cognitive radio networks. In this paper, cooperative relaying in cognitive radio networks is studied for rateless coding error-control mechanism. For a pair of primary transmitter and receiver, we find the region in which any secondary or cognitive user can cooperate with the primary user in a constructive way. A queueing theoretical model is employed to describe the underlying system parameters and to create a mathematical framework for the analysis. The throughput performance of the secondary users is maximized based on the input traffic of the primary users. Using the unique properties of rateless codes, a low-complexity relay selection mechanism is also introduced. Through the experimental analysis, we show that the proposed rateless-coding-based cooperative mechanism can perform similar to the more complicated and more costly selective-repeat automatic repeat request algorithm. The numerical analysis using the Rapid Analysis of Queueing Systems (RAQS) software package is provided to support the findings.

Spectrum sensing is a critical component for cognitive radio networks. Most of the spectrum sensing algorithms and performance analysis, however, assume that the secondary users are stationary. In this paper, we investigate the performance analysis of spectrum sensing by mobile secondary users. Two performance metrics, false alarm probability and miss detection probability, are thoroughly investigated. In addition, a new performance metric, expected transmission time, is designed to factor the secondary users' mobility. The random waypoint based mobility model is adopted for secondary users. For spectrum sensing by mobile secondary users, a critical variable is the distance between the primary user and mobile secondary users. We mathematically model this distance, and derive its probability distribution. At last, the expressions are derived for all three performance metrics, the false alarm probability, the miss detection probability, and the expected transmission time. Extensive simulations are performed, and the results are consistent with the theoretical analysis. It is concluded that the mobility of secondary users has significant impact on miss detection probability, but not on false alarm probability.

In this paper, we propose a new multiple-level power allocation strategy for the secondary user (SU) in cognitive radio (CR) networks. Different from the conventional strategies, where SU either stays silent or transmit with a constant/binary power depending on the busy/idle status of the primary user (PU), the proposed strategy allows SU to choose different power levels according to a carefully designed function of the receiving energy. The way of the power level selection at SU side is optimized to maximize the achievable rate of SU under the constraints of average transmit power at SU and average interference temperature to PU. Simulation results demonstrate that the proposed strategy can significantly improve the throughput of SU compared to the conventional strategies.

In order to effectively utilise the spectrum of wireless network, secondary users (SUs) are often authorised to share spectrum with primary users (PUs) in cognitive networks. To guarantee effective transmission of PUs and SUs, the interference from the SUs to the PUs is limited and only the SUs that have the information rates (rates) than the corresponding thresholds are allowed to transmit their data. In order to select proper SUs to transmit and to maximise their achievable weighted sum rate (WSR) under rate requirement and interference constraint, the authors propose a joint admission control and beamforming design algorithm for partial channel state information (CSI) case. The WSR maximisation problem is first constructed by using approximation and convex relaxation, according to the statistical property of the CSI. Then a penalty factor is introduced to check the feasibility of such problem and instruct the admission of the SUs. Beyond the feasible SUs set, the WSR is maximised by updating the achievable rate of each user with rate profile technique and polyblock outer approximation method. Simulation results show that the proposed beamforming can achieve higher WSR than the beamforming of the existing baseline method.

Cognitive radio networks (CRNs) have received considerable attention and viewed as a promising paradigm for future wireless networking. Its major difference from the traditional wireless networks is that secondary users are allowed to access the channel if they pose no harmful interference to primary users. This distinct feature of CRNs has raised an essential and challenging question, i.e., how to accurately estimate interference to the primary users from the secondary users? In addition, spectrum sensing plays a critical role in CRNs. Secondary users have to sense the channel before they transmit. A two-state sensing model is commonly used, which classifies a channel into either busy or idle state. Secondary users can only utilize a channel when it is detected to be in idle state. In this paper, we tackle the estimation of interference at the primary receiver due to concurrently active secondary users. With the spectrum sensing, secondary users are refrained from transmitting once an active user falls into their sensing range. As a result, the maximum number of simultaneously interfering secondary users is bounded, typically ranging from 1 to 4. This significant conclusion considerably simplifies interference modeling in CRNs. The authors present all the cases with possible simultaneously interfering secondary users. Moreover, the authors derive the probability for each case. Extensive simulations are conducted and results validate the effectiveness and accuracy of the proposed approach.

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.

Channel accessibility by a secondary user (SU) in cognitive radio networks (CRNs) depends on the availability of the spectrum based on primary user and other SU activities. A new SU request may be blocked and an ongoing SU service may also be discarded if no sufficient spectrum is available. So far, little work has been done to analyze the reliability and availability aspects of CRNs from the perspective of the dependability theory. In this paper, we introduce the concept of availability for spectrum access in multi-channel CRNs, which is defined as the fraction of time that a CRN can allocate at least the minimum number of required channels for a new SU request. Through a proposed continuous-time discrete-state Markov model, we analyze the performance of CRN channel access schemes in terms of a few reliability-relevant metrics such as mean channel available time and mean time to first channel unavailability. Furthermore numerical results are also presented in this paper and the correctness of the derived theoretical models are verified through simulations.

Cognitive Radio Networks (CRNs) provide a solution for the spectrum scarcity problem facing the wireless communications community. To be able to utilize CRNs in practical applications, a certain level of quality-of-service (QoS) should be guaranteed to the secondary users (SUs) in such networks. In this paper, we propose a packet scheduling scheme that orders the SUs' transmissions according to the packet dropping rates and the number of packets queued waiting for transmission. A medium access control (MAC) protocol, based on the mentioned scheduling scheme, is proposed for a centralized CRN. In addition, the scheduling scheme is adapted for a distributed CRN, by introducing a feature that allows SUs to organize access to the available spectrum without the need for a central unit. Extensive simulation results are presented to evaluate the proposed protocols, in comparison with other MAC protocols designed for CRNs. The results demonstrate the effectiveness of our proposed protocols to guarantee the required QoS for voice packet transmission, while maintaining fairness among SUs.

Cooperative spectrum sensing (CSS) can improve the spectrum sensing performance by introducing spatial diversity in cognitive radio networks (CRNs). However, such cooperation also introduces the delay for reporting sensing data. Conventional cooperation scheme assumes that the cooperative secondary users (SUs) report their local sensing data to the fusion center sequentially. This causes the reporting delay to increase with the number of the cooperative SUs, and ultimately affects the performance of CSS. In this article, we consider the reporting delay and formulate the optimization problem of CSS with sensing user selection to maximize the average throughput of the CRN in both the additive white Gaussian noise (AWGN) environment and the Rayleigh fading environment. It is shown that selecting all the SUs within the CRN to cooperate might not achieve the maximal average throughput. In particular, for the AWGN environment, the sensing user selection scheme is equivalent to selecting the optimal number of cooperative SUs due to all the SUs having the same instantaneous detection signal-to-noise ratio (SNR). For the Rayleigh fading environment, the maximal average throughput is achieved by selecting a certain number of cooperative SUs with the highest instantaneous detection SNRs to cooperate. Finally, computer simulations are presented to demonstrate that the average throughput of the CRN can be maximized through the optimization.

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.