Dynamic Spectrum Access Policy Research Articles

Blocking Rate Analysis in Heterogeneous Multicell Cognitive-Radio 5G Networks

Cognitive radio (CR) technology is being recognized as one of the main enabling technologies for supporting massive high-speed connectivity in multicell fifth-generation (5G) networks by allowing dynamic spectrum access policies according to predetermined etiquette. Under this paradigm, the available spectrum is opportunistically allocated to the different cells. A key metric that is heavily employed in designing efficient CR-based multicell spectrum-allocation mechanisms is the blocking rate. An efficient spectrum-allocation mechanism aims to adaptively allocate channels to the different cells such that the overall blocking rate is minimized. In this article, we use the theory of continuous-time Markov chains to derive a closed-form expression for the blocking rate in multicell CR-based 5G networks. In our derivations, we build two detailed mathematical models describing the frequency-spectrum usage of both primary and secondary users. We combine the two models in a hierarchical fashion. As opposed to related models in the literature which suffer high complexity, the proposed hierarchical structure yields simplicity and tractability. Furthermore, while existing research works overlook spectrum heterogeneity, the proposed model addresses this important factor. Simulation results demonstrate high accuracy in evaluating the blocking rate across the different cells in the network.

Blockchain Structure Electromagnetic Spectrum Database in Distributed Cognitive Radio Monitoring System

Traditional centralized electromagnetic spectrum monitoring platforms collect energy detection data from time, frequency and space dimensions. This method has high data redundancy. Combining the propagation loss characteristics and the signal direction finding (DF) data of each detection node, we focus on the signal source compressed parameter estimation. We propose a minimum average distance (MAD) method to improve the accuracy of collaborative detection in Cognitive Radio Network (CRN). The collaborative estimated data is stored in the blockchain structure to establish the distributed electromagnetic spectrum database (BC-DSDB). Based on the consensus mechanism Proof of High Confidence (POHC), the detection nodes maintain BC-DSDB independently. To regulate the rational utilization of electromagnetic spectrum resources, we propose the Spectrum Resource Currency (SRC) to evaluate the priority of the secondary user (SU) for dynamic spectrum access. When a spectrum collision event occurs between SUs, the spectrum time slice resources can be allocated according to the SRC. The experimental results show that BC-DSDB accurately describes the distribution of electromagnetic spectrum resources based on the propagation loss characteristics. At the same time, the redundancy of spectral data storage is reduced. SUs can quickly formulate dynamic spectrum access policies based on BC-DSDB and SRC in distributed cognitive radio networks.

Performance analysis of cell-based spectrum handoff in cognitive radio vehicular centralized and ad-hoc networks

Spectrum handoff (SHO) is an essential technique in dynamic spectrum access policy to guarantee seamless and robust service of a cognitive radio. Link maintenance probability (LMP), link failure probability (LFP), service completion probability (SCP), probability mass function (PMF), and expected number of SHOs are key measuring metrics to characterize SHO performances in cognitive radio vehicular centralized network (CR-VCNET) and cognitive radio vehicular ad-hoc network (CR-VANET). In this paper, we develop and model the performance measuring parameters for a non-stationary cognitive user (CU) considering both complete service and incomplete service period under two CR network situations: opportunistic situation (OS or CR-VANET) and negotiated situation (NS or CR-VCNET). This paper analyzes the impact of CU mobility and spectrum hole mobility on various performance measuring metrics to explore the characteristics and performance of the CR networks. This paper also presents the comparison results for expected number of SHOs and SCP of a CU with and without mobility in both CR-VCNET and CR-VANET. The results of performance metrics obtain for a non-stationary CU under the impact of service time distributions are significantly different for CR-VCNETs and CR-VANETs. In addition, we also present Monte-Carlo simulation of LMP, LFP, and probability mass function of SHO for a non-stationary CU to validate the proposed model.

Design Guidelines for Database-Driven Internet of Things-Enabled Dynamic Spectrum Access.

The radio-frequency spectrum shortage, which is primarily caused by the fixed allocation policy, is one of the main bottlenecks to the deployment of existing wireless communication networks, and to the development of new ones. The dynamic spectrum access policy is foreseen as the solution to this problem, since it allows shared spectrum usage by primary licensed and secondary unlicensed networks. In order to turn this policy into reality, the secondary network must be capable of acquiring reliable, real-time information on available bands within the service area, which can be achieved by means of spectrum sensing, spectrum occupancy databases, or a combination of them. This Review presents guidelines related to the design of a framework that can be adopted to foster dynamic spectrum access policies. The framework applies special-purpose Internet of Things (IoT) devices that perform spectrum sensing, subsequently feeding a spectrum occupancy database, which in turn will be used by the secondary network to gather information on location-dependent spectrum availability. The guidelines address technological enablers capable of making the framework feasible, reliable and secure.

Impact of the primary user on the secondary user blocking probability incognitive radio sensor networks

With the increasing usage of wireless sensor network technologies, their unlicensed bands become overcrowded. To address this challenge, cognitive radio technology with the dynamic spectrum access policy has merged with Wireless Sensor Network to overcome spectrum underutilization. The Cognitive Radio Sensor Network (CRSN) has emerged as a promising solution to overcome spectrum scarcity in a resource-constrained wireless sensor network. In CRSN, TCP has to cope with a new type of packet loss due to the primary users (PU) arrival, known here as a secondary user (SU) blocking loss. In this paper SU blocking loss is modelled by a discrete-time Markov chain. The experimental results are verified using the NS2.

PERIODIC SENSING AND GREEDY ACCESS POLICY USING CHANNEL MODELS WITH GENERALLY DISTRIBUTED ON AND OFF PERIODS IN COGNITIVE NETWORKS

One of the fundamental issues in the design of dynamic spectrum access policy is the modeling of the dynamic behavior of channel occupancy by primary users. Under a Markovian modeling of channel occupancy, a periodic sensing and greedy access policy is known as one of the simple and practical dynamic spectrum access policies in cognitive radio networks. In this paper, the primary occupancy of each channel is modeled as a discrete-time alternating renewal process with generally distributed on- and off-periods. A periodic sensing and greedy access policy is constructed based on the general channel occupancy model. Simulation results show that the proposed policy has better throughput than the policies using channel models with exponentially distributed on- or off-periods.

QoS provisioning energy saving dynamic access policy for overlay cognitive radio networks with hidden Markov channels

Dynamic spectrum access policy is crucial in improving the performance of overlay cognitive radio networks. Most of the previous works on spectrum sensing and dynamic spectrum access consider the sensing effectiveness and spectrum utilization as the design criteria, while ignoring the energy related issues and QoS constraints. In this article, we propose a QoS provisioning energy saving dynamic access policy using stochastic control theory considering the time-varying characteristics of wireless channels because of fading and mobility. The proposed scheme determines the sensing action and selects the optimal spectrum using the corresponding power setting in each decision epoch according to the channel state with the objective being to minimise both the frame error rate and energy consumption. We use the Hidden Markov Model (HMM) to model a wireless channel, since the channel state is not directly observable at the receiver, but is instead embedded in the received signal. The procedure of dynamic spectrum access is formulated as a Markov decision process which can be solved using linear programming and the primal-dual index heuristic algorithm, and the obtained policy has an index-ability property that can be easily implemented in real systems. Simulation results are presented to show the performance improvement caused by the proposed approach.

다른 이차사용자의 신뢰 벡터를 추적하여 이차사용자 사이의 충돌을 줄이기 위한 동적 스펙트럼 접속 방식

동적 스펙트럼 접속 방식에서 각 이차사용자는 자신의 성능을 높이기 위하여 채널의 상태를 추적하여 채널이 사용되지 않을 가능성이 가장 높은 채널을 선택하게 된다. 다수의 이차사용자가 동일한 동적 스펙트럼 접속 방식에 따라 동작한다면, 대부분의 이차사용자는 비슷한 결과의 채널 상태 추적 정보를 얻게 된다. 이로 인해 각 이차사용자가 동일한 채널을 선택할 가능성이 높아지고, 이차사용자 사이의 충돌이 발생할 가능성이 높아진다. 본 논문은 이러한 이차사용자 사이의 충돌을 줄이기 위하여 다른 이차사용자의 신뢰 벡터를 추적하여 그 결과를 채널 선택에 이용하는 동적 스펙트럼 접속 방식을 제안한다. 시뮬레이션 결과는 본 논문에서 제안한 방식이 다른 이차사용자를 고려하지 않는 방식에 비해 성능이 더 나아진다는 것을 보여준다. To achieve better performance in dynamic spectrum access networks, each secondary user tracks channels and chooses a good channel to transmit its packet. When all secondary users adopt the same dynamic spectrum access policy, they have similar channel information, which leads secondary users to choose the same channel and more collisions among them. To relieve this problem, we propose an access policy using belief vector tracking method for other competing secondary users. Simulation results are provided to show that the proposed policy yields better performance than the existing policies which do not take into account what other secondary users are doing.

A Quantitative Analysis on the Impact of Spectrum Access Policy Flexibility and DSA System Capability on Spectrum Sharing Potential

While Dynamic Spectrum Access (DSA) is premised upon the existence of technologies and policies that enable flexible access to spectrum, a quantitative understanding of the coupling among DSA system capabilities, policy definition, and spectrum sharing potential remains largely unexplored. Over ten years of technology research, development, and prototype testing has resulted in algorithms and system concept advances, including the ability to deduce policy constraints (and permissions) in situ. Knowing the constraints, however, is different than selecting operating parameters (e.g., transmission power) that lead to policy compliance (e.g., interference mitigation). The primary hurdle to in situ compliance is situational awareness uncertainty, which results from the inherently stochastic nature of wireless communications and dynamics of spectrum user activity.Situational uncertainty has a significant impact on policy specifications. Lacking trusted mechanisms for handing in situ uncertainty in DSA systems, regulators manage uncertainty and associated risk through policy specifications that impose conservative operating constraints in order to maintain high degrees of interference prevention. For example, TV Band Device policies map to “worst-case” path loss assumptions based upon the range of possible operating conditions. The result is limited spectrum sharing in the majority of operating conditions in an effort to ensure risk mitigation of significant impacts associated with rare situations.This paper asserts and tests the hypothesis that improved spectrum sharing is possible via in situ probabilistic reasoning coupled with policy specifications enabling DSA system flexibility. The assertions are based upon results of ongoing research into the relationship between DSA situational awareness uncertainty and potential DSA performance as measured by capacity gain, interference mitigation, monetary cost, and other metrics. The study is investigating the performance potential of DSA systems given policies that regulate effects (e.g., interference potential) rather than specific behaviors or system characteristics (e.g., exclusion zones or receiver sensitivity). Results demonstrate the potential to adapt DSA system behaviors to the degree of uncertainty with respect to the performance metrics: High levels of uncertainty lead to more restrictive behavior (e.g., lower transmit power) than do lower levels of uncertainty. DSA situational awareness and uncertainty assessments are derived using probabilistic Structural Causal Modeling (SCM). The probabilistic SCM approach provides a formal and systematic means for probabilistic reasoning that is built upon well-established engineering models for wireless communications and the theoretical foundation of causal networks.Results represented by the use cases studied in this effort indicate a clear gain in spectrum access as a function of increased policy flexibility and probabilistic reasoning for DSA system situational awareness. Policies that govern specific DSA mechanisms or design constraints provide limited policy flexibility and spectrum sharing potential; they similarly limit the design options available to system developers. Policies that define the desired effect (e.g., capacity goal) or impact limitations (e.g., maximum interference power) afford the greatest flexibility to a DSA system and thus the greatest potential for spectrum sharing. A DSA system’s ability to use the spectrum sharing potential is then a function of the specific situation and the DSA system’s degree of situational awareness uncertainty. Probabilistic reasoning is shown to adapt permitted behaviors such as maximum interference free transmit power (MIFTP) in accordance with observed conditions and associated degrees of uncertainty. Greater uncertainty leads to reduced spectrum access and MIFTP and greater awareness leads to increased spectrum access and MIFTP.

Optimal, heuristic and Q‐learning based DSA policies for cellular networks with coordinated access band

AbstractDue to the increasing demands for higher data rate applications, also due to the actual spectrum crowd situation, Dynamic Spectrum Access (DSA) turned into an active research topic. In this paper, we analyse DSA in cellular networks context, where a Coordinated Access Band (CAB) is shared between Radio Access Networks (RANs). We propose a Semi‐Markov Decision Process (SMDP) approach to derive the optimal DSA policies in terms of operator reward. In order to overcome the limitations induced by optimal policy implementation, we also propose two simple, though sub‐optimal, DSA algorithms: a Q‐learning (QL) based algorithm and a heuristic algorithm. The achieved reward using the latter is shown to be very close to the optimal case and thus to significantly exceed the reward obtained with Fixed Spectrum Access (FSA). The rewards achieved by using the QL‐based algorithm are shown to exceed those obtained by using FSA. Higher rewards and better spectrum utilisation with DSA optimal and heuristic methods are, however, obtained at the price of a reduced average user throughput. Copyright © 2010 John Wiley & Sons, Ltd.