Idle Spectrum Bands Research Articles

Enhancing Spectral and Energy Efficiencies in a Cognitive Radio CRAN with PUEAs

In a cloud radio access network, malicious users mitigate the attributes of primary users in order to occupy a specific idle spectrum band by sending false signals or carry out a denial of service attack. Moreover, with the increase in number of users and limited spectral and energy resources, the malicious users will compete for the spectrum with legitimate users, thus resulting in increase in spectrum scarcity problem. The most widely used defense approach against malicious users is the received signal strength method. However, harmful users can still imitate signal attributes and transmit powers of the primary users. Therefore, in order to elaborate the best method to tackle this vulnerability and hence make more spectrum available, the modified adaptive orthogonal matching pursuit localization algorithm is proposed to detect harmful users existing in the network. However, in order to elaborate the convergence speed of the proposed method, the regularized particle filter algorithm is applied to evaluate the performance of the modified adaptive orthogonal matching pursuit under real-time conditions. The restricted isometry property is used for the performance evaluation. Further, spectral and energy efficiencies are used in the simulation results for performance evaluation, in order to observe spectrum and energy utilization efficiencies. The simulation results show that the proposed method is better in terms of computational complexity, spectral efficiency, and energy efficiency compared to other matching pursuit approaches.

Multi-Agent Learning and Bargaining Scheme for Cooperative Spectrum Sharing Process

Recently, the lack of spectrum resources has become a key technical bottleneck to develop the Industrial Internet of Things (IIoT). Based on cognitive radio technology, the cognitive IIoT (CIIoT) paradigm can improve spectrum utilization via opportunistically accessing the idle spectrum bands. In this study, a novel cooperative spectrum sharing scheme is presented for the CIIoT system platform. The main challenge of our scheme is to effectively share the limited spectrum resource via cooperative sensing and dynamic accessing techniques. To achieve a mutually desirable solution for different CIIoT devices, we design a learning game model using the ideas of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">multi-agent reinforcement learning (MARL)</i> and the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">negotiated aspirations bargaining solution (NABS)</i> . In the learning mechanism, individual CIIoT devices adaptively select their cooperative sensing policy according to the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MARL</i> model. In the bargaining mechanism, the available spectrum resource is dynamically shared through the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">NABS</i> , which is obtained based on the devices’ selected sensing policy. By investigating the contribution of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MARL</i> to game theory, the proposed scheme can effectively guide intelligent CIIoT devices toward a socially optimal outcome. Numerical simulation results demonstrate that the normalized device payoff, CIIoT system throughput and device fairness of our approach are better than those of existing benchmark protocols. Finally, we present the key challenges and future direction of our research in the CIIoT system operations.

A Game-Theoretical Learning Approach for Spectrum Trading in Cognitive Satellite-Terrestrial Networks

This letter investigates the bandwidth allocation problem for discontinuous frequency bands in cognitive satellite-terrestrial networks (CSTNs). Different from existing studies, we take the realistic assumption that the available idle spectrum bands are disconnected. Most of the existing works focused on the continuous bandwidth allocation problem and proposed corresponding algorithms optimizing continuous variables, which cannot directly solve the bandwidth allocation problem for discontinuous frequency bands. Besides, we also take the individual bandwidth requirement, the priority of terrestrial cognitive users, and the limitation on the total available bandwidth into consideration. The bandwidth allocation for discontinuous frequency bands is formulated as a bandwidth auction game, which is proven to have at least one pure strategy Nash Equalization (NE) solution. Furthermore, an improved best response learning algorithm based on exploration and exploitation (BREE) is proposed to achieve satisfying performance. Finally, simulations are conducted to verify the convergence and superiority of the proposed BREE algorithm.

Recent Advances on Sub-Nyquist Sampling-Based Wideband Spectrum Sensing

Cognitive radio (CR) is a promising technology enabling efficient utilization of the spectrum resource for future wireless systems. As future CR networks are envisioned to operate over a wide frequency range, advanced wideband spectrum sensing (WBSS) capable of quickly and reliably detecting idle spectrum bands across a wide frequency span is essential. In this article, we provide an overview of recent advances on sub-Nyquist sampling-based WBSS techniques, including compressed sensing-based methods and compressive covariance sensing-based methods. An elaborate discussion of the pros and cons of each approach is presented, along with some challenging issues for future research. A comparative study suggests that the compressive covariance sensing-based approach offers a more competitive solution for reliable real-time WBSS.

RETRACTED ARTICLE: Cooperative spectrum sensing in wireless sensor networks using forager bee’s intelligence

Increasing utilization of wireless sensor networks Leads scarcity problems in spectrum allocation channels. The development of cognitive radio networks over wireless spectrum technology based on both licensed and unlicensed user. The maximum interference of users are mitigated to use unlicensed bandwidth. Due the high interference of bandwidth sharing enormously by secondary users (SUs). To sense the unlicensed user on over problematic condition remains the overhead problems on cognitive radio networks. In this paper, Co-operative spectrum sensing as well as spectrum allocation with Forager Bee’s Intelligence algorithm is used. The idle spectrum band in licensed band is identified and allocated to sensor nodes, which reduces the interference and collisions in WSN and avoids packet retransmission. This ensures fair energy in WSNs and Spectrum resources are utilized efficiently.

A modified energy detection based dynamic spectrum sharing technique and its real time implementation on wireless platform for cognitive radio networks

Cognitive radio offers a flexible and efficient utilization of radio frequency resources by dynamic spectrum sharing as required in next gen (5G) architecture of wireless communication. The channel allocation time, probability of false alarm detection and spectral efficiency are the major performance parameters to characterize a spectrum sharing technique. This paper presents modified energy detection based dynamic channel allocation technique based on sensing the power spectral density of idle spectrum bands i.e. spectrum hole. Receiver operating characteristics (ROC) curves have been used to analyze the detector performance of sensing with respect to probability false alarm at different values of SNR. Allocation of unoccupied bands to the SUs has been done by coalition based cooperative game, which provides SUs with an incentive to cooperate. Based on their worth, SUs get payoffs which have been computed using Shapely values as a one-point solution. Vickrey–Clarke–Groves (VCG) auction mechanism has been used to allocate the spectrum resources fairly to each user. On the basis of allocation time, the present model for dynamic spectrum access appears to be more efficient as compared to the conventional opportunistic spectrum access model.

Spectrum-Occupancy Aware Cooperative Spectrum Sensing Using Adaptive Detection

In this paper, an efficient adaptive detection scheme is proposed for cognitive radio networks where multiple secondary users (SUs) cooperate to identify idle spectrum bands. Each SU generates a binary local decision, which is then transmitted either directly or via the assistance of intermediate relays to a cognitive radio base station (CRBS), where the global decision is made. The fusion process at the CRBS is performed using the local binary decisions made by the individual SUs. The local binary decisions at the relays and CRBS are regenerated based on dynamic thresholds, which are chosen to minimize the probability of the spectrum sensing error (PSSE) by considering the imbalanced nature of the spectrum occupancy, as well as the reliability of the decisions made by the SUs. The PSSE performance is derived where a closed-form analytical expression is obtained. The analytical results corroborated by Monte Carlo simulation show that using adaptive detection can reduce the PSSE significantly as compared to the conventional detection approach.

Optimized secondary user selection for quality of service enhancement of Two-Tier multi-user Cognitive Radio Network: A game theoretic approach

Cognitive Radio Networks (CRN) is the solution for the spectrum scarcity problem, that has surfaced with the exponential increase in number of mobile users. In CRN, the cognitive devices sense the spectrum, and transmits, on detecting an available channel. Thus CRN resourcefully utilize the idle spectrum bands. In CRN, the users are classified into two types - Primary users and Secondary users. Secondary users are further classified into two tiers- Real Time users (RT) and Non-Real Time users (NRT). Users from both the tiers share a single channel for transmission, resulting in efficient spectrum usage. However, with ever growing number of secondary mobile users having diverse QoS requirements, the cognitive interactions among them need to be optimized. This paper uses game theory to study the conflict and cooperation among the two tiers of secondary users. An auction game model is proposed that analyzes the complex decision making process and efficiently allocates an idle channel to a pair of RT and NRT secondary users from a pool of users. The game model is further extensively analyzed mathematically, using Markov chain, showing a reduction in user Blocking probability, user Dropping probability, Channel Saturation probability and increase in user Acceptance probability, compared to the Basic One-Tier CRN and Non-Optimized Two-Tier CRN. The optimized network model is then simulated using Qualnet 7.1. The simulation result shows improved Bandwidth Utilization Efficiency, Spectral efficiency and increased number of secondary users served, compared with respect to Basic One-Tier CRN and Non-Optimized Two-Tier CRN.

Improving the quality of service for users in cognitive radio network using priority queueing analysis

Through cognitive radio (CR), unlicensed users can occupy idle spectrum bands without interference with the primary user (PU). Generally, when the arrival rate of licensed users is high, secondary users (SUs) may starve. In this study, the authors propose two models to improve the average total waiting time for the SU. They are the M/D/1 model of a PU delay system with non-pre-emptive priority and pre-emptive priority. They are compared to an M/D/1 model with PU delay. Numerical analysis and Monte Carlo simulations are performed for all results. Improvements in the average total waiting time of 13–18% for PU and 24–32% for SU in the non-pre-emptive priority scheme are obtained. In the pre-emptive priority scheme, 19–22 and 5–7% improvements are obtained for the PU and SU respectively. Furthermore, same models, but with finite buffer capacity for both users are investigated to model a real-time system. In these schemes, the system improves the average total waiting time by 20–42% for the PU and 34–42% for the CR with the non-pre-emptive priority. Similarly, the pre-emptive model shows 25–44 and 6–24% reduction in the PU and SU waiting times respectively.

Design and Implementation of VoIP Based Two-Tier Cognitive Radio Network for Improved Spectrum Utilization

Cognitive radio networks (CRN) have paved the way toward the increase in spectrum utilization through opportunistic usage of available idle spectrum bands. However, its capacity is bounded by various factors, including channel characteristics, licensed user behavior, application requirements, etc. Currently, a fixed upper bound of the system capacity in CRN limits further progress in research in this domain. The work in this paper aims to solve this problem by introducing the concept of ‘two-tier CRN’ that not only increases overall system capacity but also allows the system to host diverse applications, thereby initiating a new direction of future research in this discipline. This paper provides the novel design approach for VoIP based two-tier CRN with every detail of formulation of the framework. The complex interaction among primary and secondary users in the proposed system is studied extensively in mathematical, simulation, and Markov models. Performance evaluation confirms 300% improvement in link utilization and, hence, higher network throughput in a two-tier CRN as compared with a basic one-tier CRN. Finally, the practical significance of the designed network is established by successfully implementing it in a test bed based disaster management system.

Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework

In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the $\epsilon $ –NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.

Utility-driven relay for hybrid access femtocells based on cognitive radio spectrum auction

Femtocells promisingly improve coverage and spectrum efficiency at the edge of macrocell. However, macro users may suffer dead-zone trouble due to strong interference coming from closed access femtocell, or compete spectrum resource with femto users in the open access model. In this paper, we propose a novel utility-driven relay scheme adopted by hybrid access femtocell (HAF) to address the above two issues, wherein the macrocell maximizes the usage of its idle spectrum bands, bided by femtocells, via cognitive radio spectrum auction; and recompense relay expense to stimulate selfish femtocells undertaking HAFs to relay the signal to the vicinal macro user, meanwhile avoiding two-tier interference. Spectrum competition among femtocells is formulated as a static Cournot game provided with global information; then necessarily considered as a dynamic Cournot game of the strategy adapting distributively according to the players previous actions. Furthermore, we introduce a protocol and propose refund factor, spectrum price dynamic adjustment algorithms to achieve the Stackelberg equilibrium, i.e., the solution of the non-cooperative game between macrocell and femtocells. We also prove the existence of equilibrium and the convergence of algorithms. Extensive simulation results show the details of games, which indicate they can match the win-win hybrid access mechanism, benefiting cell-edge macro users for better QoS and higher access opportunities for femto users.

Distortion-Aware Dynamic Channel Allocation for Multimedia Users in Cognitive Radios

Cognitive radio has been developed recently as a promising solution to tackle the spectrum related issues such as spectrum scarcity and spectrum underutilization. Cognitive spectrum assignment is necessary for allocating spectrum bands to secondary users in order to avoid conflicts among secondary users and maximize the total network performance under a given set of conditions. In most spectrum assignment schemes, throughput is considered as the main criterion for spectrum selection or spectrum assignment. In this paper, we propose a distortion-aware channel allocation scheme for multiple secondary users who compete for primary channels to transmit multimedia data. In the proposed scheme, idle spectrum bands are assigned to the multimedia secondary users that attain the highest video distortion reduction. The scheme is expected to mitigate the selfish behaviors of users in competing channels. The performance effectiveness of our proposed channel allocation scheme is demonstrated through simulation by comparing with a benchmark of two reference spectrum assignment schemes.

Analytical modeling for spectrum handoff decision in cognitive radio networks

Cognitive Radio (CR) is an emerging technology used to significantly improve the efficiency of spectrum utilization. Although some spectrum bands in the primary user’s licensed spectrum are intensively used, most of the spectrum bands remain underutilized. The introduction of open spectrum and dynamic spectrum access lets the secondary (unlicensed) users, supported by cognitive radios; opportunistically utilize the unused spectrum bands. However, if a primary user returns to a band occupied by a secondary user, the occupied spectrum band is vacated immediately by handing off the secondary user’s call to another idle spectrum band. Multiple spectrum handoffs can severely degrade quality of service (QoS) for the interrupted users. To avoid multiple handoffs, when a licensed primary user appears at the engaged licensed band utilized by a secondary user, an effective spectrum handoff procedure should be initiated to maintain a required level of QoS for secondary users. In other words, it enables the channel clearing while searching for target vacant channel(s) for completing unfinished transmission. This paper proposes prioritized proactive spectrum handoff decision schemes to reduce the handoff delay and the total service time. The proposed schemes have been modeled using a preemptive resume priority (PRP) M/G/1 queue to give a high priority to interrupted users to resume their transmission ahead of any other uninterrupted secondary user. The performance of proposed handoff schemes has been evaluated and compared against the existing spectrum handoff schemes. Experimental results show that the schemes developed here outperform the existing schemes in terms of average handoff delay and total service time under various traffic arrival rates as well as service rates.

PERFORMANCE ANALYSIS OF COGNITIVE NETWORK WITH PRIMARY AND SECONDARY CHANNELS

Abstract. We consider a cognitive network with a primary and a sec-ondary channel. Primary users have higher priority on the usage of theprimary channel, and secondary users are allowed to opportunisticallyaccess the primary channel at times when the channel is not occupiedby primary users. The secondary channel is dedicated only to secondaryusers. An analytical model is presented to obtain the performance ofan opportunistic spectrum access using both the primary and secondarychannels, and is validated by simulations. 1. IntroductionReports of spectrum eciency reveal that a considerable region of the spec-trum remains unused. As a solution for such inecient spectrum usage, op-portunistic spectrum access (OSA) has been intensively studied. Under thissystem, a secondary user that does not have a license to use the spectrum isallowed to opportunistically occupy an idle spectrum band owned by a licenseethat is termed by the primary user [1, 2]. Much attention has been paid to thequality-of-service of secondary users. Wang et al. [3] proposed two cognitiveMAC schemes to support voice services in the presence of primary users. Lee[4] developed a simple approximate model for unslotted OSA networks undernon-saturation conditions. Considering prioritization among secondary users,Lee [5] proposed an OSA scheme with channel reservation for high prioritysecondary users and bu ering for low priority secondary users.This paper considers a cognitive network with a primary and a secondarychannel. Primary users have higher priority on the usage of the primary chan-nel, and secondary users are allowed to opportunistically access the primarychannel at times when the channel is not occupied by primary users. Thesecondary channel is dedicated only to secondary user. The main objective of

Designing a Markov Model for the Analysis of 2-tier Cognitive Radio Network

Cognitive Radio Network (CRN) aims to reduce spectrum congestion by allowing secondary users to utilize idle spectrum bands in the absence of primary users. However, the overall user capacity and hence, the system throughput is bounded by the total number of available idle channels in the system. This paper aims to solve the problem of limited user capacity in basic CRN by proposing a 2-tier CRN that allows another tier (or layer) of secondary users to transmit, in addition to the already existing set of primary and secondary users in the system. Markov Models are designed step-wise to map the interaction between primary and secondary users in both tiers by including suitable traffic distribution models and system parameters. Spectrum handoff is also incorporated in the developed Markov Models. Performance analysis is carried out in terms of SU transmission, dropping, blocking and handoff probabilities along with mathematical formulation of the overall SU throughput in 2-tier CRN. It confirms better spectrum utilization in spectrum handoff enabled 2-tier CRN over basic CRN with enhancement in quality of service for secondary users in terms of reduced dropping and blocking probabilities.

Optimal distributed power allocation for a new spectrum sharing paradigm in cognitive radio networks

The problem of power allocation in cognitive radio networks plays an important role to improve the efficiency of spectrum utilization. However, most of previous works focus on the power allocation for secondary users in spectrum sharing overlay or spectrum sharing underlay, which needs to frequently handoff between the idle spectrum bands or considers the interference constraints in all spectrum bands respectively. In order to reduce the handoff and fully utilize the spectrum resource, we propose a new spectrum sharing paradigm which not only can just need to adjust the transmit power in spectrum bands instead of frequently handoff between idle spectrum bands, but can fully utilize the spectrum resource as we only consider the interference power constraints in active spectrum bands rather than in all spectrum bands. Then based on this new spectrum sharing paradigm and the constraint conditions, we study the distributed power allocation for secondary users and formulate the optimization problem as a non-cooperative game problem, after that the variational inequality approach is used to solve this game problem and a Nash equilibria solution is got, finally simulation results are illustrated to demonstrate the performance of the proposed scheme.

MAP: Multiauctioneer Progressive Auction for Dynamic Spectrum Access

Cognitive radio (CR) is a promising paradigm to achieve efficient utilization of the limited spectrum resource by allowing the unlicensed users to access the licensed spectrum, and dynamic spectrum access (DSA) is one of the fundamental functions of CR networks. Market-driven spectrum auction has been recognized as an effective way to achieve DSA. In spectrum auction, the primary spectrum owners (POs) act as auctioneers who are willing to sell idle spectrum bands for additional revenue, and the secondary users (SUs) act as bidders who are willing to buy spectrum bands from POs for their services. However, conventional spectrum auction designs are restricted within the scenario of single auctioneer. In this paper, we study the spectrum auction with multiple auctioneers and multiple bidders, which is more realistic for practical CR networks. We propose MAP, a Multiauctioneer Progressive auction mechanism, in which each auctioneer systematically raises the trading price and each bidder subsequently chooses one auctioneer for bidding. The equilibrium is defined as the state that no auctioneer and bidder would like to change his decision. We show analytically that MAP converges to the equilibrium with maximum spectrum utilization of the whole system. We further analyze the incentive for POs and SUs joining the auction and accepting the auction result. Simulation results show that MAP well converges to the equilibrium, and the spectrum utilization is arbitrary closed to the global optimal solution according to the length of step.