Primary User Band Research Articles

An artificial intelligence‐based spectrum sensing methodology for LoRa and cognitive radio networks

SummaryThe artificial intelligence‐based spectrum sensing approach is extremely important in terms of effective bandwidth utilization for low power wide area networks (LPWANs) based on cognitive radio networks (CRNs). Most studies perform spectrum detection with CRNs using optimization or deep neural network methods. However, optimization‐based spectrum detection approaches based on current LPWANs are scarce. For this purpose, in this study, a hybrid optimization methodology integrated with CRNs is proposed for LoRa, which is one of the most compatible LPWAN technologies in the Internet of Things (IoTs) recently. In the particle swarm optimization (PSO) part of this hybrid methodology, agent users are created so that secondary users (SUs) could use the licensed band of primary users (PUs) in cognitive radio. On the genetic algorithm side, LoRa error rates are minimized in order to further improve the performance of the proposed method. In this way, effective spectrum sensing is performed in the LoRa network. Various LoRa‐CRN experiments have been carried out in the simulation environment, and the probability of detection and false alarm performances have been compared with both theoretical and proposed approaches in terms of quality estimation parameters. It is clear from the results that the proposed methods give successful results for the LoRa‐CRNs.

Optimized MAC Protocol Using Fuzzy-Based Framework for Cognitive Radio AdHoc Networks

Cognitive radio networks (CRNs) have been widely used in various applications for effective radio spectrum utilization in recent years. It is essential to fend off the growing demand for this finite natural resource for next-generation communications. In CRNs, detecting the activity of the primary user requires opportunistic spectrum sensing for efficient usage of the available radio spectrum, which is a limited and exquisite resource. Thus, CRNs are the key component in solving the spectrum scarcity issue in the presence of primary user bands through secondary users. Cognitive radio AdHoc networks (CRAHNs) are a unique kind of CRNs where infrastructures less cognitive radio (CR) nodes are furnished. In CRAHN, the CR-MAC protocol works slightly differently from the traditional wireless network MAC protocols. Particularly, the proposed method includes a high traffic scenario under contention-based IEEE 802.11 DCF MAC protocol. Accordingly, it can be observed that both, throughput and delay, increase as the CW size and packet length of the 802.11 (DCF) MAC protocol for CRAHN varies. Therefore, this paper proposed a fuzzy-based optimization framework for the 802.11 (DCF) MAC protocol in CRAHNs. Furthermore, it optimized throughput and delay by training a database of input parameters, contention window, and packet length for the Mamdani and Sugeno fuzzy inference system (FIS) models of the 802.11 (DCF) protocol simultaneously. The experimental result of the proposed framework for CRAHN with FIS shows that altering the contention window increases throughput by 25% and reduces the delay by 38% compared to the IEEE802.11 (DCF) protocol for CRAHNs without FIS. Moreover, it is also revealed that the throughput is increased by and 7% and the delay is reduced by 40% to 50% due to altering the packet length.

Analysis of the Impact of Detection Threshold Adjustments and Noise Uncertainty on Energy Detection Performance in MIMO-OFDM Cognitive Radio Systems.

Due to the capability of the effective usage of the radio frequency spectrum, a concept known as cognitive radio has undergone a broad exploitation in real implementations. Spectrum sensing as a core function of the cognitive radio enables secondary users to monitor the frequency band of primary users and its exploitation in periods of availability. In this work, the efficiency of spectrum sensing performed with the energy detection method realized through the square-law combining of the received signals at secondary users has been analyzed. Performance evaluation of the energy detection method was done for the wireless system in which signal transmission is based on Multiple-Input Multiple-Output—Orthogonal Frequency Division Multiplexing. Although such transmission brings different advantages to wireless communication systems, the impact of noise variations known as noise uncertainty and the inability of selecting an optimal signal level threshold for deciding upon the presence of the primary user signal can compromise the sensing precision of the energy detection method. Since the energy detection may be enhanced by dynamic detection threshold adjustments, this manuscript analyses the influence of detection threshold adjustments and noise uncertainty on the performance of the energy detection spectrum sensing method in single-cell cognitive radio systems. For the evaluation of an energy detection method based on the square-law combining technique, the mathematical expressions of the main performance parameters used for the assessment of spectrum sensing efficiency have been derived. The developed expressions were further assessed by executing the algorithm that enabled the simulation of the energy detection method based on the square-law combining technique in Multiple-Input Multiple-Output—Orthogonal Frequency Division Multiplexing cognitive radio systems. The obtained simulation results provide insights into how different levels of detection threshold adjustments and noise uncertainty affect the probability of detection of primary user signals. It is shown that higher signal-to-noise-ratios, the transmitting powers of primary user, the number of primary user transmitting and the secondary user receiving antennas, the number of sampling points and the false alarm probabilities improve detection probability. The presented analyses establish the basis for understanding the energy detection operation through the possibility of exploiting the different combinations of operating parameters which can contribute to the improvement of spectrum sensing efficiency of the energy detection method.

Throughput Maximization of a UAV Assisted CR Network With NOMA-Based Communication and Energy-Harvesting

The performance of an unmanned aerial vehicle (UAV) assisted cooperative cognitive radio (CR) network is studied in this paper. The study is carried out for line-of-sight (LOS) links between UAV and a ground user and UAV aerodynamic power consumption of UAV. The UAV consists of an RF energy harvester and it is also a CR enabled device. It harvests energy from RF signal of source nodes. It rotates periodically over a circular region of interest (CROI) for finding the vacant primary user (PU) band. It uses a PU band to set a link between ground nodes, while the direct links between them suffer from severe fading. The decision about the status of a PU band is made cooperatively. In cooperative sensing, all the sources along with the UAV take sensing decisions and send them to fusion centre (FC). A two stage fusion scheme is proposed to take the overall decision. The considered network model uses non-orthogonal multiple access (NOMA) scheme to forward the information of a source to its corresponding destination. Analytical expressions of harvested energy, overall sensing decision and throughput are developed. The analytical expressions capture the effect of fading as well as change in distances (source-UAV and UAV-destination) due to the circular flight of the UAV. Impact of imperfect successive interference cancellation (SIC) on the system performance is also studied. Power allocation in the second hop link is optimized to maximize the network throughput. Energy-efficiency of the considered network is evaluated. For a given UAV flight period, radius of the circular trajectory, and the velocity of the UAV is optimized to maximize the energy-efficiency. Sensing performance of the considered system model is studied in terms of false alarm. Network throughput is investigated for several network parameters such as fading parameter, the number of sources, the number of UAV's sensing slots, the velocity of UAV, the radius of the UAV trajectory etc. Sensing angle and harvesting angle are optimized to maximize the throughput. Results show that the value of fading parameter, radius of UAV trajectory, and UAV velocity has significant impact on throughput. The performance of NOMA is compared with orthogonal multiple access (OMA).

On the Retrial-Queuing Model for Strategic Access and Equilibrium-Joining Strategies of Cognitive Users in Cognitive-Radio Networks with Energy Harvesting

This article studies the strategic access of single-server retrial queue with two types of customers, where priority is given according to their category. On the basis of this concept, a cognitive-radio network was developed as retrial queue with energy harvesting. Cognitive radio allows for a secondary user to opportunistically access the idle spectrum of a primary user (PU). Upon arrival of a primary user, the service given to the secondary user by the cognitive radio is interrupted, and the PU band is available for the primary user. After completion of service for the primary user, the PU band is again available to secondary users. Performance metrics are derived to study the equilibrium strategies of secondary users. A Stackelberg game was formulated and Nash equilibrium was derived for the noncooperative strategy of the secondary user. Game-theory concepts are incorporated with queuing theory ideas to obtain the net benefit for the noncooperative strategy and social benefit for cooperative strategy. Lastly, analytical results are verified with numerical examples, and the effects of energy-harvesting rate are discussed.

Allocation of optimal energy in an energy-harvesting cooperative multi-band cognitive radio network

This paper studies the achievable total throughput of an energy harvesting cooperative cognitive radio (CR) network. A CR transmitter cooperates with a primary user (PU) transmission if PU is found to be present in the given channel while it transmits its own data in the absence of PU. The CR transmitter is an energy harvesting node which harvests simultaneously from non-RF signal as well as RF signal of PU. The CR transmitter uses the harvested energy on shared basis for cooperation and transmission. The same study is also extended for cooperation of multiple CRs in multiple PU band scenario. In cooperation in muti-band scenario, all CRs sense all PU channels and sensing informations are fused at fusion centre to know about the status of PU. Performance is investigated in terms of total network throughput for several parameters such as sensing time, energy splitting parameter, and energy allocation ratio etc. Novel analytical expressions for total useful throughput and optimal energy allocation ratio parameter under the considered network scenario are developed. Useful throughput and optimal energy allocation ratio parameter are also estimated for a target secondary network (CR network) throughput under a quality of service constraint of PU such as collision probability. It is observed that the value of optimal energy allocation parameter gets reduced if the number of CRs in cooperation increases or the number of PU channels increases.

Power allocation for multiuser precoded OFDM cognitive radio

The high sidelobe leakage from the transmitted signals in orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) has always been a subject of concern, particularly when the OFDM-based CR users and the licensed primary users (PUs) coexist in adjacent frequency bands. Orthogonal precoding in OFDM-based CR systems is an effective spectral shaping technique that can significantly reduce this sidelobe leakage in adjacent PU band(s). In this paper, we propose an optimal power allocation scheme which is augmented with orthogonal precoding-based spectral shaping for multiuser OFDM CR systems. The precoding is realized on a user basis such that the transmitted multiuser OFDM signal and its first few derivatives become time-continuous. The objective of the proposed (precoded OFDM) optimal power allocation scheme is to maximize the downlink sum data rate of all users in the OFDM-based CR system, while the interference introduced to PUs is maintained below predefined thresholds and the transmit power of CR base station transmitter is kept within its power budget. Through simulation results, we demonstrate that the proposed precoded OFDM optimal power allocation scheme can deliver much higher sum data rate of CR users in comparison to the conventional (uncoded OFDM) optimal power allocation scheme and the precoded OFDM uniform power allocation scheme. Further, whereas the computational complexity of the precoded OFDM uniform power allocation scheme is the least, the proposed precoded OFDM optimal power allocation scheme has computational advantage over the conventional uncoded OFDM optimal power allocation scheme.

Efficient idle channel discovery mechanism through cooperative parallel sensing in cognitive radio network

■■■Finding holes from the underutilized portion of spectrum at various times and locations is the most important function in cognitive radio networks (CRNs). This requires efficient sensing policy at the MAC layer that can discover more idle channels in less time. Whereas, the sensing policy depends on the channel sensing order that decides how a secondary user senses the primary user band in minimum period of time. Spectrum sensing policies for searching idle channels from the underutilized primary band can significantly affect the performance of secondary user in terms of throughput, reliability, and energy efficiency. In this paper, we have analyzed MAC protocol structure for ad hoc radio networks which used random channel sensing. This results in poor performance, either due to the channels being skipped or the time for sensing the band being significantly longer. We propose a parallel sensing scheme with sequential channel selection order as part of MAC protocol, which can discover all the free channels in the primary user band in less time. For the proposed scheme, we have performed analysis over the number of channels sensed and the number of idle channels discovered. Furthermore, energy efficiency and throughput of the system have also been evaluated. The results show considerable improvement for the proposed scheme when compared with the contemporary scheme.

A novel channel state prediction technique for overlay cognitive radio-based emergency sensor networks

For overlay cognitive radio (CR), this paper proposes a knowledge-based spectrum prediction technique using artificial neural network. This is targeted for CR-based emergency sensor networks in real life applications, where extremely reliable data transmission is mandatory. The technique operates in two steps: 1) identification of idle states in primary user bands; 2) prediction of noise level of the idle bands. The goal is to select a less noisy vacant band among the detected idle bands. The system is analysed under both Gaussian mixer noise (GMN) distribution and additive white Gaussian noise (AWGN) by predicting the current state of the channel in low SNR environment. Simulation results using MATLAB R2015b show satisfactory values for probability of false alarm (0.17 and 0.3), and probability of misdetection (0.12 and 0.25) for AWGN and GMN, respectively.

A Novel Channel State Prediction Technique for Overlay Cognitive Radio-based Emergency Sensor Networks

For overlay cognitive radio (CR), this paper proposes a knowledge-based spectrum prediction technique using artificial neural network. This is targeted for CR-based emergency sensor networks in real life applications, where extremely reliable data transmission is mandatory. The technique operates in two steps: 1) identification of idle states in primary user bands; 2) prediction of noise level of the idle bands. The goal is to select a less noisy vacant band among the detected idle bands. The system is analysed under both Gaussian mixer noise (GMN) distribution and additive white Gaussian noise (AWGN) by predicting the current state of the channel in low SNR environment. Simulation results using MATLAB R2015b show satisfactory values for probability of false alarm (0.17 and 0.3), and probability of misdetection (0.12 and 0.25) for AWGN and GMN, respectively.

Optimal Service Rate in Cognitive Radio Networks With Different Queue Length Information

Cognitive radio (CR) technology effectively overcomes spectrum inefficiency by providing the capability that unlicensed users can share the radio frequency spectrum with licensed users. In this paper, we consider a CR system with heterogeneous users. A single primary user (PU) randomly generates service requests and a licensed band processes these requests. This PU band also can be flexibly accessed by secondary users (SUs) if available. The CR system is regarded as a preemptive priority queueing system. Under different information levels, we investigate the equilibrium strategic behaviors of PU and SUs. Based on users’ strategies, we study SU’s sojourn time (i.e., the period beginning from the time an SU request enters the system and ending from the time the SU request is completed), and obtain the analytical solutions of SU’s mean sojourn time. By theoretical and numerical analysis, the SU’s mean sojourn time is found not decreasing with the service rate of PU. This phenomenon is counterintuitive, and it implies the increase of the service rate of PU does not necessarily reduce the mean sojourn time of SU. In this sense, we investigate and find optimal service rates of PU in different information levels to meet the PU’s QoS requirement and simultaneously to maximize SU’s throughput from the viewpoint of the service providers.

Strategic spectrum occupancy for secondary users in cognitive radio networks with retrials

AbstractThis article investigates joining strategies and admission control policy for secondary users (SUs) with retrial behavior in a cognitive radio (CR) system where a single primary user (PU) coexists with multiple SUs. Under a certain reward‐cost structure, SUs opportunistically access the PU band when it is not occupied by the PU. If the band is available upon arrival, an SU decides with a probability either to use the band immediately or to balk the system. If the band is occupied, the SU must decide whether to enter the system as a retrial customer or to leave the system. Once the PU requests for service, the service of SU being served, if any, will be interrupted, and the interrupted SU leaves the band and retries for service after a random amount of time. In this article, we study the equilibrium behavior of non‐cooperative SUs who want to maximize their benefit in a selfish, distributed manner with delay‐sensitive utility function. The socially optimal strategies of SUs are also derived. To utilize the PU band more efficiently and rationally, an admission control policy is proposed to regulate SUs who enter the system in order to eliminate the gap between the individually and socially optimal strategies.

Strategic behavior and admission control of cognitive radio systems with imperfect sensing

This paper conducts the game-theoretic analysis of the behavior of secondary users (SUs) in a cognitive radio (CR) system with a single primary user (PU) band and sensing failures. It is assumed that the sensing errors occur only when an SU is being served by the PU band. It may incorrectly detect there is no PU accessing to the band (called misdetection), or it may wrongly sense that there is an incoming PU but in fact it is not true (called false alarm). When a misdetection occurs, the PU will be blocked and the ongoing SU will drop into a retrial pool called orbit in which it can retry for service after some random time. When a false alarm occurs, the ongoing SU will drop into the retrial orbit. That is, both errors will degrade the quality of service of the system. First, we investigate how the arriving SUs make decisions on whether to join or balk the system which can be studied as a non-cooperative game. We obtain the equilibrium behavior of SUs who want to maximize their benefit in a selfish distributed manner. Second, we derive the socially optimal strategies of SUs from the perspective of the social planner. To use the PU band more efficiently, an appropriate admission fee imposed on each joining SU is proposed based on the gap between the equilibrium strategy and the socially optimal strategy. Finally, theoretic results are validated by numerical analysis and the effect of various parameters on the behavior of SUs is illustrated.

Strategic Joining and Optimal Pricing in the Cognitive Radio System With Delay-Sensitive Secondary Users

The transmission times with generally random distributed for both primary user (PU) and secondary user (SU) in a cognitive radio system with a single PU band is investigated. To characterize the random access protocols of wireless networks, a retrial queueing system is employed to model the decentralized and centralized behavior of SUs. Based on the tradeoff between the service reward and the delay cost, each SU must decide whether to join or balk the system upon arrival based on different levels of information provided by the system. Two situations in which SUs have no information or partially observable information are studied. In each situation, two kinds of strategies are considered: 1) individual equilibrium strategies (i.e., non-cooperative strategies) that maximize SUs’ own profit and 2) socially optimal strategies (i.e., cooperative strategies) that maximize the expected social welfare. Moreover, comparisons are carried out between these two kinds of strategies. The results indicate that the equilibrium joining probability in the non-cooperative case is not less than the optimal joining probability in the cooperative case. To regulate the SUs’ behavior, an equilibrium pricing scheme is proposed to make these strategies coincide. In addition, we observe that the expected delay and the mean number of SUs in the system only depend on the first two moments of the SU’s transmission time. Numerical examples also show that the partially observable queue is more profitable from the perspective of the social planner.

Throughput Analysis of Full-Duplex Communication Cognitive Radio Network

In this paper we deal with the throughput of full-duplex cognitive communication radio which exploits unused band of primary user (PU) network. Classical cognitive radio uses half-duplex communication spectrum sensing to perform spectrum sensing and data transmission at different time intervals. It’s well-established fact that in half-duplex communication cognitive radio spectrum sensing time increases at low SNR which gives rise to lesser data transmission time for secondary user (SU) and hence results in less throughput for SU. It’s useful idea to do spectrum sensing and data transmission at the same time with two different antennas co-located on the SU transceiver. This shall not only guarantee high probability of detection of PU but also increased data transmission which means more throughput for SU. However, simultaneous sensing and data transmission has inherent problem of self-interference. One of the possible solution is to use polarisation discrimination in which sensing and data transmission antennas must use different polarisation. This is feasible if there is prior information about the polarisation of the signals emitted by the PUs. It shall be of special interest to assess throughput using analytical expressions for probability of detection P_D, probability of false alarm P_{FA} at various values of SNR for time-slotted cognitive radio which uses half-duplex spectrum sensing and non-time-slotted cognitive radio which uses full-duplex communication cognitive radio.

Traffic-Aware Green Cognitive Radio

Cognitive Radio Network (CRN) has emerged as an effective solution to the spectrum under-utilization problem, by providing secondary users (SUs) an opportunistic access to the unoccupied frequency bands of primary users (PUs). Most of the current research on CRN are based on the assumption that the SU always has a large amount of data to transmit. This leads to the objective of SU throughput maximization with a constraint on the allowable interference to the PU. However, in many of the practical scenarios, the data arrival process of the SU closely follows an ON–OFF traffic model, and thus the usual throughput optimization framework may no longer be suitable. In this paper, we propose an intelligent data scheduling strategy which minimizes the average transmission power of the SU while maintaining the transmission delay to be sufficiently small. The data scheduling problem has been formulated as a finite horizon Markov Decision Process (MDP) with an appropriate cost function. Dynamic programming approach has been adopted to arrive at an optimal solution. Our findings show that the average transmitted power for our proposed approach can be as small as 36.5% of the power required for usual throughput maximization technique with insignificant increase in average delay.

Cognitive Multihoming System for Energy and Cost Aware Video Transmission

To alleviate the spectrum scarcity problem in the licensed cellular networks (LCNs), we introduce a new paradigm called cognitive multihoming (CM), where a cognitive radio (CR)-enabled base station transmits to the users simultaneously over the licensed cellular bands and primary user bands in CR networks (CRNs). The CR aspect incurs lower cost, however, at the expense of higher energy consumption due to intermittent channel sensing. On the other hand, transmission via LCN is expensive because of its licensing premium. To minimize the transmission cost while meeting the users energy and received video quality constraints, sensing duration and transmission rate over CRN, transmission rate over LCN, and network selection for retransmission of lost packets are adjusted. Solution to the multiuser resource allocation optimization problem is obtained by solving the cost minimization problem of a single-user system. The problem is nonconvex which is solved using convex-concave procedure. The proposed scheme is compared with the cases where a user operates over a single network, either LCN or CRN. The system performance results indicate that the proposed CM strategy significantly decreases the cost to the users as well as serves a higher number of users while maintaining the desired video quality and energy consumption constraints.

Noncooperative and Cooperative Joining Strategies in Cognitive Radio Networks With Random Access

A cognitive radio (CR) system with retrial possibility and an admission cost for secondary users (SUs) to join the retrial group is investigated in this paper. If the SU finds the primary user (PU) band unavailable, it must decide with a probability estimate to either enter a retrial group or give up its service and leave the system. SUs in the retrial group independently retry after an exponentially distributed random time until they successfully access the spectrum. When the PU arrives, the SU's service on the band is interrupted. This interrupted SU is then assumed to occupy the PU band immediately when the PU completes its service. First, the noncooperative joining behavior of SUs that choose to maximize their benefit in a selfish distributed manner is investigated, and an inefficient Nash equilibrium is derived. Second, from the perspective of the social planner, the socially optimal joining strategy when SUs cooperate with each other is studied, and the corresponding Nash equilibrium is exactly derived. Finally, the result that an individually optimal strategy, in general, does not yield the socially optimal strategy is theoretically verified. Furthermore, to bridge the gap between the individually and socially optimal strategies, a novel strategy of imposing an admission fee on SUs to join the retrial group is proposed and investigated with the derivation of an optimal value for the admission fee. The numerical analysis indicates that the proposed admission fee as an equilibrium strategy and the socially optimal strategy of SUs improve efficiency in the utilization of the CR system.

Game-theoretic analysis of opportunistic spectrum sharing with imperfect sensing

We consider the strategic behavior of secondary users (SUs) in a cognitive radio system where SUs opportunistically share a single primary user (PU) band over a coverage area. The service of an SU can be interrupted by a PU in a preemptive manner, and the interrupted SU may abandon the system or wait until the PU band is sensed available. In the latter case, if spectrum sensing errors occur, they will cause misdetections and false alarms which impact the system’s performance heavily. In this paper, we model this problem as a retrial queueing system with server breakdowns and recoveries in which the interrupted SUs are treated as retrial customers. They will retry for using the PU band after some period of time due to interruptions or misdetections. The arrival of a PU during service of an SU is modeled as a server breakdown, and the recovery time is equivalent to the service time of this PU. We focus on the behavior of arriving SUs who can make decisions on whether to join the system or to balk based on a natural cost structure and the delays caused by PUs’ interruptions, which can be studied as a non-cooperative game. The equilibrium and optimal strategies of SUs are both derived. Furthermore, to bridge the gap between the individually and socially optimal strategies, a novel strategy of imposing an admission fee on SUs to join the retrial group is proposed. Finally, some numerical examples are presented to show the effect of several key parameters on the system performance.

A Spectral Distance Based Power Control Scheme for Capacity Enhancement of OFDM Cognitive Radio

This work investigates power allocation algorithms for capacity maximization of a non-contiguous orthogonal frequency division multiplexing (NC-OFDM) based cognitive radio (CR) user coexisting with multiple active primary users (PU), under total power budget, sub-channel power and overall interference constraints. Based on the spectral distance between specific subcarriers and PU bands, the scheme allocates power among a minimum number of PU adjacent subcarriers with a water level that is different from the `far-away' subcarriers. The proposed `n-adjacent' approach is subjected to both aggregate and individual PU band interference constraint. Unlike some of the existing methods, the proposed method is capable of meeting the constraints including the contribution of `good quality' subcarriers even when they are close to PU bands. Comparison of results for a wide range of power budget shows that the improved method, using the same complexity, can achieve higher cognitive user capacity with greater power allocation efficiency.