Idle Channel Research Articles

Reinforcement learning‐based spectrum handoff scheme with measured PDR in cognitive radio networks

Spectrum handoff plays an important role in cognitive radio networks (CRNs). Secondary users (SUs) use spectrum handoff to hold on the idle channel or to free the channel for primary users (PUs). Spectrum handoff scheme greatly affects the transmission quality and the success rate of SUs connection. In this Letter, a reinforcement learning-based spectrum handoff scheme with the measured packet drop rate (PDR) for multimedia transmissions over CRNs is proposed. In a system model with multiple PUs and SUs, a new state space description method is designed and an observed state includes not only the status whether PUs arrive on each channel but also several other important factors. Also, the measured PDR, instead of the calculated one, is presented to update the mean opinion score, the Q-table and the handoff policy. Compared with the existing schemes with the calculated PDR from the Quality-of-Experience model, the authors' proposed scheme can converge more rapidly in the dynamic radio environment, and reduce the PDR of SUs more significantly.

Performance Analysis of Delay-Constrained Traffic in a Cognitive Radio Network With RF Energy Harvesting

We consider a cognitive radio network where a secondary user (SU) tries to opportunistically access the channel time unused by the primary users (PUs) to transmit real-time status update packets with delivery deadline. For the radio frequency (RF)- powered SU, the channel occupancy times of the PUs are opportunities to harvest energy, whereas the idle channel times are opportunities to transmit data. Thus, there is a balance characterizing the SU performance in terms of channel occupancy probability of the PUs. We investigate the timely-delivery probability of data packets for the RF-powered SU. Specifically, we reveal the impact of the PU's channel occupancy probability on the timely-delivery probability and packet sojourn time.

Hybridized Fuzzy Based Clustering For Wireless Sensor Networks Based On Cognitive Internet Of Things

Wireless sensor network explosive growth has increased demand for radio spectrum and has created problems with spectrum shortage since different wireless services and technologies have already been assigned the full range of wireless sensor networks. Cognitive radio has become a promising solution for resource-controlled wireless sensor network to access the reserved under-used frequency bands resourcefully. Artificial intelligence algorithms allow sensor nodes to avoid crowded congested bands by detecting under utilized licensed bands and to decide to adapt their transmission parameters. However, clusters are based on fixed spectrum distribution and cannot deal with the dynamic spectrum allocation required for future generation networks. Clusters are used to reduce power usage and support scalability of sensor networks. This article proposes an Hybridized Fuzzy Clustering (HFC), which groups adjacent nodes with comparable sets of idle channels and optimally forming power-efficient clusters based on three fuzzy energy parameters, proximity to the base station, and the level of the node to determine the possibility of each node being a cluster head.

A secured and reliable communication scheme in cognitive hybrid ARQ-aided smart city

Due to advancements in communication technologies, specifically, the Internet of Things (IoT)-based smart cities, the allocation of spectral bands is a major challenge. To overcome this challenge, the cognitive radio network (CRN) has widely been accepted for efficient utilization of the available spectrum. Hence, efficient spectrum utilization and secured communication have attracted significant attention in recent years. However, due to the involvement of smart wireless devices in CRN, the cognitive radio (CR) systems are vulnerable to security threats that mainly target the weaknesses of CR communication and networking. Considering the efficient utilization of spectrum and secured smart city applications, this paper proposes a Secured and Reliable Cognitive Hybrid Automatic Repeat reQuest (SRC-HARQ) scheme. The SRC-HARQ models the primary user (PU) channel by Hidden Markov Model (HMM) to identify the unoccupied spaces. Based on the HMM results, the cluster head (CH) in a smart city determines the activity pattern of PUs and detects idle channels. After the detection of an idle channel, the CH broadcasts a beacon. Upon the reception of a beacon, each member node responds with a ready-to-send (RTS) message along with an encrypted message. The CH replies with a clear-to-send (CTS) signal after the successful decryption of the received message. Furthermore, a 4-state Markov Chain is used for reliability in terms of false alarm and misdetection. The closed-form expressions for mean packet delay, end-to-end delay, and throughput are derived and validated using Monte Carlo simulations.

Thermal-difference states of light: Quantum states of heralded photons

We introduce the thermal-difference states (TDS), a three-parameter family of single-mode non-Gaussian bosonic states whose density operator is a weighted difference of two thermal states. We show that the states of "heralded photons" generated via parametric down-conversion (PDC) are precisely those among the TDS that are nonclassical, meaning they have a negative $P$-function. The three parameters correspond in that context to the initial brightness of PDC and the transmittances, characterizing the linear loss in the signal and the idler channels. At low initial brightness and unit transmittances, the heralded photon state is known to be a single-photon state. We explore the influence of brightness and linear loss on the heralded state of the signal mode. In particular, we analyze the influence of the initial brightness and the loss on the state nonclassicality by computing several measures of nonclassicality, such as the negative volume of the Wigner function, the sum of quantum Fisher information for two quadratures, and the ordering sensitivity, introduced recently by us [Phys. Rev. Lett. 122, 080402 (2019)]. We argue finally that the TDS provide new benchmark states for the analysis of a variety of properties of single-mode bosonic states.

Beam Selection and Discrete Power Allocation in Opportunistic Cognitive Radio Systems With Limited Feedback Using ESPAR Antennas

We consider an opportunistic cognitive radio (CR) system consisting of a primary user (PU), secondary transmitter (SUtx), and secondary receiver (SUrx), where SUtx is equipped with an electrically steerable parasitic array radiator (ESPAR) antenna with beam steering capability for sensing and communication, and there is a limited feedback channel from SUrx to SUtx. Taking a holistic approach, we develop a framework for integrated sector-based spectrum sensing and sector-based data communication. Upon sensing the channel busy, SUtx determines the beam corresponding to PU's orientation. Upon sensing the channel idle, SUtx transmits data to SUrx, using the selected beam corresponding to the strongest channel between SUtx and SUrx. We formulate a constrained optimization problem, where SUtx- SUrx link ergodic capacity is maximized, subject to average transmit power and interference constraints, and the optimization variables are sensing duration, thresholds of channel quantizer at SUrx, and transmit power levels at SUtx. Since this problem is non-convex we develop a suboptimal computationally efficient iterative algorithm to find the solution. Our numerical results quantify the capacity improvement provided by the ESPAR antenna and demonstrate that our CR system yields lower outage and symbol error probabilities, compared with a CR system that its SUtx has an omni-directional antenna.

NOMA‐based cooperative relaying for secondary transmission in cognitive radio networks

In this study, the authors present and investigate a novel cooperative relaying scheme for cognitive radio networks (CRNs), which is based on non-orthogonal multiple access (NOMA). In the proposed scheme, following the detection of an idle channel, the secondary base station transmits a power domain NOMA signal to a first nearby secondary user (SU). In addition to decoding its own signal, this user applies a decode-and-forward strategy to relay the signal intended to a second SU. In contrast to previous works, where the spectrum sensing and transmission phases are treated separately, the authors here consider both phases jointly in the design and analysis of the proposed scheme. To characterise performance of the latter, analytical expressions are derived for the outage probability and the ergodic rate of the two SUs by assuming a flat Rayleigh fading channel model. The performance of two traditional orthogonal multiple access schemes is also analysed for comparison. Simulation and numerical results are presented to demonstrate the effectiveness of the proposed cooperative relaying scheme for CRN, as well as the accuracy of the analytical results.

PROLEMus: A Proactive Learning-Based MAC Protocol Against PUEA and SSDF Attacks in Energy Constrained Cognitive Radio Networks

Malicious users can exploit vulnerabilities in cognitive radio networks (CRNs) and cause heavy performance degradation by denial of service (DoS) attacks. During operation, cognitive radios (CRs) spend a considerable amount of time to identify idle (free) channels for transmission. In addition, CRs also need additional security mechanisms to prevent malicious attacks. Proactive model predictive control (MPC)-based medium access control (MAC) protocols for CRs can quicken the idle channel identification by predicting future states of channels in advance. This provides enough time for CRs to carry out other calculations like DoS attack detection. However, such external detection techniques use additional power that makes them inappropriate for energy constrained applications. As a solution, this paper proposes a proactive learning-based MAC protocol (PROLEMus) that shows immunity to two prominent CR-based DoS attacks, namely, primary user emulation attack (PUEA) and spectrum sensing data falsification (SSDF) attack, without any external detection mechanism. PROLEMus shows an average of 6.2%, 8.9%, and 12.4% improvement in channel utilization, backoff rate, and sensing delay, respectively, with low prediction errors (≤1.8%) saving 19.65% energy, when compared to recently proposed MAC protocols like ProMAC aided with additional DoS attack detection mechanism.

RAACM: Resource Allocation for Admission Control in MANET

As wireless mobile network becomes widespread, the demand for user application is higher and the services provided by the wired application is expected to be available in the wireless medium. Therefore, the users of these applications will expect the same quality of service (QoS) obtained in wired network. Providing a reliable QoS in wireless medium, especially mobile ad-hoc network (MANET), is quite challenging and remains an ongoing research trend. The key issue of MANET lies around the ability to accurately predict the needed and available resources to avoid interference with ongoing traffic. An essential solution to the issues posed by MANET is the introduction of an admission control component for a guaranteed QoS. Admission control helps to control the usage of resources when an additional service is requested. For an admission decision to be made for a new flow, the expected bandwidth consumption must be correctly predicted prior to admission, notwithstanding the fact that wireless medium is shared and nodes contends among themselves to access the medium. The novelty of this research work is the proposed resource allocation for admission control in MANET (RAACM) solution which is an admission control scheme that estimates the available bandwidth needed within a network using a robust and accurate resource estimation technique. Furthermore, the various factors that must be considered for an effective estimation were highlighted and simulations were carried out. Results obtained show that our proposed scheme for MANET outperforms existing state-of-the-art approaches for admission control with bandwidth estimation. Part of this success is associated with its assumption about the idle channel period, which prevents the overestimation and underestimation of the existing bandwidth measurement. RAACM considers the dependency of two adjacent node idle channel occupancy by differentiating the networks BUSY state from the SENSE BUSY state and the IDLE state caused by an empty queue to give a better estimation.

An integrated scheme for streaming scalable encoded video-on-demand over CR networks

In this paper, we propose an adaptive scheme to deliver scalable VoD streams over a cognitive radio network (CRN) that consists of a base station (BS) and multiple secondary users (SUs). The proposed scheme aims at improving the perceptual quality of the received videos at the SUs end while maintaining a continuous playback. To do so, the scheme opportunistically exploits the idle primary channel(s) as sensed by the BS. Moreover, to reduce the impact of the intermittent availability nature of the CR channels, we propose a channel allocation algorithm that fairly allocates the idle channel(s) among the active SUs while jointly taking into consideration the status of the playback buffers at the SUs as well as the quality of the available channels. Additionally, the proposed scheme schedules the video frames on the allocated slots by exploiting the flexibility of the scalable video encoder as well as the adaption of the used modulation level based on the channel conditions to meet a predetermined target bit error rate (BER). Simulation results demonstrate the efficiency of the proposed scheme in exploiting the scalability feature of the transmitted video sequences to efficiently use the dynamic CR resources while achieving improved peak signal-to-noise ratio of the reconstructed video streams with uninterrupted playback.

MPMAC: Clustering Based MAC Protocol for VANETs

Vehicular safety messaging is warranted mostly in turbulent traffic situations in which even cluster based MAC protocols are beset by problems of cluster rupture, which leads to non-availability of channels to vehicles even when channels are idle. To solve this, motion parameters based cluster medium access (MPMAC) protocol is presented in this paper. The vehicles organize themselves into headless clusters without any messaging. The members of a cluster are not spatially bunched and may belong to different lanes. Each cluster has channels earmarked with the flexibility of utilizing idle channels belonging to other clusters. Safety messages are accorded higher priority with one channel dedicated exclusively for these messages. To enhance channel utilization and avoid the hidden station problem, the RSU monitors the channels and periodically advertises the channel usage map. The MPMAC protocol increases the system’s throughput by enhancing channel utilization and facilitates the availability of channels during traffic conditions like phantom jams, lane changing and congestion. The delivery of safety messages to intended vehicles is ensured make provisions for flexible and prioritized channel access in addition to an earmarked channel. Simulation results show that the proposed MPMAC protocol is able to provide sufficient channels for dissemination of safety and other messages with enhanced throughput, fair access, and increased channel utilization while minimizing cluster formation overheads.

Fuzzy inference based adaptive channel allocation for IEEE 802.22 compliant smart grid network

Smart grid (SG) uses bi-directional communication among the components of power system all the way from generation down to power consumers. The basic architecture of SG is comprised of multi-layered network with applications that have diverse quality-of-service (QoS) requirements. Integrating cognitive radio (CR) in SG network results in efficient handling of differential data amounts and latencies, while meeting stringent reliability requirements through cognition in the system parameters and bandwidth adaptation. Meeting data rate, reliability, and latency demands of various smart grid applications pose greater challenge in presence of uncertainty factors e.g. spectrum sensing errors, channel unavailability with desired parameters and signal-to-noise ratio etc. Spectrum sensing is the fundamental requirement of any CR-based network and this is required to identify available idle channels. Existing channel selection algorithms do not consider exact SG communication requirements simultaneously to allocate a suitable channel in accordance with some wireless standards. In this paper, we propose a technique which selects the optimum channel for the particular application, from a pool of available channels which best meets the QoS requirements. For the optimum channel selection, fuzzy inference system optimization technique is used. The physical layer is based on mode-4 of IEEE 802.22 standard, wireless regional area network. A novel approach is also proposed for allocation of channel when desired channel in not available. This approach is based on selecting an alternate channel, in event of unavailability of desired channel, with parameters that closely match with the desired requirements in order to reduce re-transmission probability. The proposed technique outperforms existing algorithms in terms of achieved latency by a minimum of 200%, and throughput by approximately 50%.

A Spectrum-Aware Priority-Based Link Scheduling Algorithm for Cognitive Radio Body Area Networks.

With the development of wireless communication technology, wireless body area networks (WBANs) have become a fundamental support tool in medical applications. In a real hospital scenario, however, the interference between wireless medical devices and WBANs may cause a high packet drop rate and high latency, which is harmful to patients using healthcare services. Nonetheless, cognitive radio is a promising technology for sharing the precious spectrum, which has high efficiency of the wireless resource. Thus, WBANs with cognitive radio capability are also exploited. We propose a spectrum-aware priority-based link scheduling (SPLS) algorithm for cognitive radio body area networks (CRBANs) in a real hospital scenario. In SPLS, three channels are used: DataCh, EDataCh, and CtrlCh for normal data, emergency data, and control messages, respectively. To avoid collision during data transmission, neighboring CRBANs send messages regarding the channel state with CtrlCh before the scheduling. The CRBANs can share DataCh in the time domain for improving the throughput. The SPLS algorithm allows a CRBAN to access idle channels on the licensed and unlicensed spectrum according to the CRBAN traffic. Our simulation results show that the proposed SPLS outperformed the conventional scheme in terms of packet delivery ratio, system throughput, latency, and energy efficiency.

A matrix analytic approach to study the queuing characteristics of nodes in a wireless network

In this paper, we propose a model to study the queueing characteristics of nodes in a wireless network in which the channel access is governed by the well known binary exponential back off rule. By offering the general phase type (PH) distributional assumptions to channel idle and busy periods and assuming Poisson packet arrival processes at nodes, we represent the model as a quasi birth death process and analyse it by using matrix analytic methods. Stability of the system is examined. Several important queueing characteristics that help in efficient design of such systems are derived. Extensive simulation analysis is performed to establish the validity of our theoretical results.. It is shown that both the simulated and theoretical results agree on some important performance measures. Some real life data has been used to get approximate PH representations for channel idle and busy period variates, which in turn are used for numerical illustrations.

Spectrum Access Issues and Security in Cognitive Radio Network

Advanced cognitive radio networks (CRNs) are a promising technology. This network functions to solve the issue of scarcity of the radio spectrum by allocating the idle channels. It also carefully allocates the spectrum to unlicensed users in a balanced approach. The expediency of cognitive radio is highly reliant on fair and efficient supervision of the access to the idle portion of frequency channels. This is mainly executed by the network layer and media access control layer of the internet network model. There are various technical and communication issues while intelligently allocation spectrums to high priority and low priority channels. The current article performs a detailed analysis of such challenging issues and technical feasibility of implementing security measures in CRN applications in a systematic order. So, the problem statement of the current research article is a systematic analysis of channel access issues and their proposed solutions using improved protocols.

Joint bandwidth and power allocation for multiple services in TV white space

As the bandwidth resource in TV white space (TVWS) is permitted to be used for the secondary users, multiple secondary networks coexisting in the same geographical area can provide multiple services without interfering with the primary service, such as the TV broadcasting. To satisfy the minimum rate requirements and maximise the sum rate of the multiple services, the problem of resource allocation can be modelled as a mixed integer non-linear programming (MINLP). According to this model, the joint bandwidth and power allocation (JBPA) method is proposed to solve the resource allocation for multiple services. The JBPA method is sub-optimal, which can approximate the performance of the optimal two-step exhaustive search (TSES) method very well, especially when the number of services is larger than the number of idle channels. Compared with TSES, the JBPA method decreases the complexity from exponential level to polynomial level. Besides, compared with one channel occupied by single service, the JBPA can serve more services and provide stable performance when the number of services varies dynamically. Compared with the algorithm random bandwidth allocation, the JBPA can approximate the optimal performance provided by TSES better with the time complexity of the same order.

Spectrum management with simultaneous power‐controlled assignment decisions in cognitive radio networks

SummarySpectrum sharing protocols for cognitive radio networks (CRNs) are often designed based on an exclusive channel occupancy policy. This policy does not allow concurrent cognitive radio (CR) transmissions to take place over the same channel. Unfortunately, this can significantly affect spectrum utilization and network performance. Allowing several secondary users to simultaneously share the same channel naturally improves spectrum utilization and avoids unnecessary blocking of CR transmissions. The key challenge in enabling efficient operation of multichannel CRNs is how to perform efficient power‐controlled media‐access‐control (MAC) protocols. These protocols include both power control and channel assignment. In this paper, we propose a power‐controlled MAC protocol for CRNs based on interference‐channel occupancy model with the objective of maximizing the number of served CR transmissions. It uses a novel power‐controlled channel assignment mechanism that allows several concurrent interference‐limited transmissions to simultaneously proceed over each idle channel in the same neighborhood. We present two variants of the power‐controlled channel assignment mechanism. The first proposed variant is suitable for CRNs with fixed data packet size, whereas the other is suitable for dynamic CRNs with variable packet size. The second variant of our protocol employs a users' scheduling procedure that attempts to fully utilize the available time‐frequency blocks. Simulation results indicate that employing transmission power control along with appropriate channel assignment and users' scheduling in CRNs can significantly improve the spectrum utilization and the overall network performance.

Idle Channel Detection Scheme under Impulsive Noise Environments

Idle Channel Detection Scheme under Impulsive Noise Environments

An Enhanced MPR OLSR Protocol for Efficient Node Selection Process in Cognitive Radio Based VANET

A VANET is an excellent instance of a wireless sensor network. The mobile vehicles are the nodes and communication happens between the vehicular nodes. This facility of communicating with the vehicular nodes finds varied applications ranging from entertainment to emergency services. When combined with cognitive radio techniques, VANETs are equipped with the facility of sensing the spectrum opportunistically. When the spectrum is sensed efficiently, the channel and the bandwidth can be utilized effectively. To achieve this, we have coordinated the enhanced Optimal Link State Routing Protocol (MMPR-OLSR) with the GSA-PSO (Gravitational Search-Particle Swarm Optimization) scheme in combination with the cognitive radio technique. This technique can be applied to the Vehicular Sensor Networks. MMPR-OLSR with GSA-PSO optimization facilitates the MMPR-OLSR protocol to select the suitable member nodes using an optimal searching technique. The GSA-PSO optimization not only helps in choosing the appropriate MMPR nodes, but also helps in reducing the unnecessary overheads due to the propagation of the control packets. By selecting the appropriate MMPR nodes. It is also possible to minimize the number of relay selector nodes used in transmission. The optimization technique also focuses on assigning the channels among all the network users. This is controlled by our proposed approach. A group of nodes are selected before the start of the actual transmission. These vehicular nodes within the communication range are used as relays in the transmission. These nodes are categorized as Multi Point Relays. Cognitive radio plays an active role by identifying the idle channels, thus enabling the usage of the unused channels. Our proposed approach works efficiently in achieving the objective of effective channel utilization combined with efficient transmission. Our proposed approach is simulated using the NS2 platform and is evaluated based on important network metrics. Our proposed method shows a sharp decrease in delay and a high packet delivery ratio in addition to a high channel utilization. The proposed GSA-PSO approach decreases the delay associated with packet transmission and delivery in VANETs and also ensures a good PDR due to the effective channel utilization.

Research on Uneven Clustering APTEEN in CWSN Based on Ant Colony Algorithm

In this paper, APTEEN is applied to cognitive wireless sensor networks, and an ant colony-based uneven clustering APTEEN algorithm (ACUCAPTEEN) is proposed. The algorithm combines routing and spectrum allocation with cross-layer design method, improves energy efficient uneven clustering protocol and introduces it to APTEEN, and uses ant colony algorithm to complete inter-cluster path search, which reduces the task of cluster head. In the candidate cluster head selection process, the residual energy is not considered and the competition radius is fixed, so that the nodes with many idle channels but low residual energy become cluster heads, and the cluster heads far away from the base station still have more intra-cluster tasks with less residual energy. For these problems, an optimized ACUCAPTEEN algorithm(OACUCAPTEEN) is proposed to optimize the candidate cluster heads, the residual energy is taken as a factor of the candidate cluster head probability, and the competition radius is optimized. The simulation results show that the ACUCAPTEEN algorithm and optimization algorithm can reduce the node death rate and extend the network life cycle.