Wireless Regional Area Network Research Articles

Performance Analysis of Cooperative Spectrum Sensing using Empirical Mode Decomposition and Artificial Neural Network in Wireless Regional Area Network

Background: Radio spectrum is natural and the most precious means in wireless communication systems. Optimal spectrum utilization is a key concern for today's cutting-edge wireless communication networks. The impending problem of the lack of available spectrum has prompted the development of a new idea called “Cognitive Radio” (CR). Cooperative spectrum sensing (CSS) is utilized to improve the detection performance of the system. Several fusion algorithms of decision-making are proposed for sensing the licensed user, but they do not work well under low signal-to-noise ratio (SNR). Objectives: To address the issue of poor detection performance under low SNR, Empirical mode decomposition (EMD) and artificial neural network (ANN) based CSS under Rayleigh multipath fading channel in IEEE 802.22 wireless regional area network (WRAN) is proposed in this paper. Method: In this work, we propose the use of ANN as a fusion center. First, the received signal's energy is calculated using EMD. The computed energy, SNR, and false alarm probability are combined to form a data set of 2048 samples. They are utilized to train Levenberg- Marquardt back propagation training algorithm-based feed-forward neural network (FFNN). Using this trained network, CSS in WRAN is simulated under Rayleigh multipath fading. Results: Simulation results show that the proposed CSS method based on EMD-ANN outperforms the standard fast Fourier transform (FFT) and EMD detection-based cooperative spectrum sensing with a hard "OR" fusion at low SNR. With Pf =0.01, 100% detection accuracy with proposed techniques is obtained at SNR= -22dB. Conclusion: The findings show that the suggested approach outperforms EMD and FFT based energy detection scheme-based traditional CSS in low SNR environments.

Artificial Neural Network Based Spectrum Sensing in Wireless Regional Area Network

Artificial Neural Network Based Spectrum Sensing in Wireless Regional Area Network

Improvement in spectrum sensing of wireless regional area network with empirical mode decomposition

Improvement in spectrum sensing of wireless regional area network with empirical mode decomposition

Toward the Coexistence of Cognitive Networks for Vehicular Communications on TVWS for IEEE Std. 802.22

The IEEE 802.22 is a standard for wireless regional area networks to opportunistically operate in TV bands; however, sharing TV White Space (TVWS) spectrum creates a problem of coexistence because no mechanism is defined for coordinating channel usage among secondary networks. We propose a White Space Resource Sharing mechanism (WSRS) for fixed secondary and mobile IEEE 802.22 networks to improve network coexistence and spectrum efficiency. Based on power control and channel allocation, our mechanism allows the TVWS system to serve vehicular networks in scenarios where there are active secondary fixed networks and no more TVWS channels available for opportunistic usage. Unlike state-of-the-art mechanisms for coexistence in TVWS spectrum, our mechanism allocates resources to vehicles even when the density of fixed nodes and the transmission power of the fixed network cause high interference to the vehicular network. Our results show the offered channel capacity increases up to 50% using the proposed WSRS mechanism compared to the recent IEEE 802.22 standard that does not have a defined TVWS channel sharing mechanism. Furthermore, our WSRS mechanism implements a strategy to protect the fixed secondary network from interference caused by vehicular transmissions while promoting fair usage for both secondary networks.

Hybrid Spectrum Sensing Using MD and ED for Cognitive Radio Networks

Day by day, the demand for wireless systems is increasing while the available spectrum resources are not sufficient. To fulfil the demand for wireless systems, the spectrum hole (spectrum vacant) should be found and utilised very effectively. Cognitive radio (CR) is a device which intelligently senses the spectrum through various spectrum-sensing detectors. Based on the complexity and licensed user’s information present with CR, the appropriate detector should be utilised for spectrum sensing. In this paper, a hybrid detector (HD) is proposed to determine the spectrum hole from the available spectrum resources. HD is designed based on an energy detector (ED) and matched detector (MD). Unlike a single detector such as ED or MD, HD can sense the signal more precisely. Here, HD can work on both conditions whether the primary user (PU) information is available or not. HD is analysed under heterogeneous environments with and without cooperative spectrum sensing (CSS). For CSS, four users were used to implement OR, AND, and majority schemes under low SNR walls. To design the HD, specifications were chosen based on the IEEE Wireless Regional Area Network (WRAN) 802.22 standard for accessing TV spectrum holes. For the HD model, we achieved the best results through OR rule. Under the low SNR circumstances at −20 dB SNR, the probability of detection (PD) is maximised to 1 and the probability of a false alarm (PFA) is reduced to 0 through the CSS environment.

Girth aware normalized min sum decoding algorithm for shorter length low density parity check codes

Recently, short block codes are in great demand due to the emergent applications requiring the transmission of a short data unit and can guarantee speedy communication, with a minimum of latency and complexity which are among the technical challenges in today’s wireless services and systems. In the context of channel coding using low density parity check (LDPC) codes, the shorter length LDPC block codes are more likely to have short cycles with lengths of 4 and 6. The effect of the cycle with the minimum size is that this one prevents the propagation of the information in the Tanner graph during the iterative process. Therefore, the message decoded by short block code is assumed to be of poor quality due to short cycles. In this work, we present a study of the evolution of the messages on check nodes during the iterative decoding process when using the LDPC decoding algorithm normalized min sum (NMS), to see the destructive effect of short cycles and justify the effectiveness of the girth aware normalized min sum (GA-NMS) decoding LDPC codes algorithm in terms of correction of the errors, particularly for the codes with short cycles 4 and 6. In addition to this, the GA-NMS algorithm is evaluated in terms of bit error rate performance and convergence behavior, using wireless regional area networks (WRAN) LDPC code, which is considered as a short block code.

Cooperative Spectrum Sensing under SISO and MIMO Environment for Cognitive Radio Networks

Background: Increasing demand for wireless devices leads to the efficient use of spectrum resources. Despite the limited availability of spectrum resources, all licensed users do not utilize their spectrum all the time. Objective: Cognitive Radio (CR) is used to detect free channels in the available spectrum resources and access them dynamically without interfering with licensed users. Various spectrum sensing (SS) techniques are available to sense the spectrum of licensed users. Methods: The spectrum sensing technique, energy detector (ED), is analysed under a Rayleigh fading channel. Further, Single Input Single Output (SISO) and Multiple Input Multiple Output (MIMO) channel models are developed in the consumer environment. The ED technique is further analysed with cooperative spectrum sensing (CSS) to overcome detection problems for a single CR user. Results: The ED achieves a probability of detection (PD) of 0.9 and a probability of false alarm (PFA) of 0.1 at the lowest SNR of −20 dB, which is the requirement for a standard IEEE 802.22 Wireless Regional Area Network (WRAN). Conclusion: Various receiver operating characteristics are determined by conducting practical simulations and theoretical calculations for each SISO and MIMO channel model with and without the CSS scenario to achieve the target PD and PFA .

Modeling and delay performance analysis of wireless regional area networks under incumbent coexistence and self‐coexistence with multichannel operations

SummaryIncumbent coexistence and self‐coexistence are common among wireless regional area networks (WRANs) using TV white space (TVWS) due to their large coverages and opportunistic spectrum access. Among incumbents of WRANs are wireless microphones (WMs) whose frequent ON–OFF activities result in intermittent availability of transmission channels. In this work, WRANs under self‐coexistence in addition to incumbent coexistence are modeled for queueing analysis using two‐dimensional (2D) Markov chains taking into account intermittent channel availability for multichannel operations. The proposed models are created based on the widely used ON–OFF Markov chain model for an individual transmission channel. The Markov chain structures depend on the number of WRANs under self‐coexistence as well as the number of transmission channels. In order to reduce the computational complexity associated with a large number of channels, truncated Markov chain models are proposed so that the scenarios with more channels than WRANs can be analyzed with the same complexity as the scenarios with the same number of channels and WRANs. The matrix geometric method is used to numerically compute steady‐state probabilities of the Markov chain, which are then used to evaluate the mean packet delay performance. These results are then used to quantify the mean packet delay obtained from channel sharing among WRANs under self‐coexistence with multichannel operations. Finally, the impact of varying the number of channels as well as varying the ON‐OFF durations of each channel on the delay performance is observed.

LNA Prototype at 54 MHz to 88 MHz Using Discrete Components

This paper presents a design and prototyping of a Low-Noise Amplifier (LNA) for Wireless Regional Area Network (WRAN) operating in TV broadcast bands between 54 MHz – 88 MHz. The LNA design was then implemented by using discrete components. Components values was obtained by utilized DC analysis according to specifications which follows the Institute of Electrical and Electronics Engineering (IEEE) 802.22 standard on WRAN technical specifications. Simulation with 88 MHz produced S11 = -5.72 dB, S12 = -41.57 dB, S21 = 15.07 dB, S22 = -4.76 dB, Noise Figure (NF) = 3.9 dB, Input Third Order Intercept Point (IIP3) = 2.21 dBm, and power consumption of 45.39 mW. Experiments results on 88 MHz showed S11 = -6.13 dB and S21 = 0.74 dB.

Employing sensor network based opportunistic spectrum utilization for agricultural monitoring

In this work, a cognitive Wireless Regional Area Network (WRAN) technology-based sensor network for agricultural monitoring is proposed. In WRAN technology, a Consumer Premise Equipment (CPE) and a base station communicate through incumbent channels opportunistically without causing any harmful interference to incumbent operations. Because CPE in IEEE 802.22 WRAN is considered as a fixed device, CPE with sensing capability is suitable for wireless sensor network environment in agriculture monitoring where there is no need for node mobility. The proposed network model consists of terrestrial and underground networks. In terrestrial network, CPEs employ Time Division Multiple Access (TDMA) technique with the purpose of sensing environmental data such as temperature, pressure, etc. and transmitting them to the base station. In the underground network, underground sensor nodes use Carrier Sense Multiple Access (CSMA) technique with the aim of sensing underground data such as humidity, soil mineral, etc. and transmitting them to the base station via cluster heads. After obtaining the analytical model of the proposed network, the simulation model of the network is carried out using Riverbed Modeler. The graphical results prove the validity and applicability of the proposed network in terms of throughput and energy consumption without any spectrum cost for agricultural monitoring in rural areas.

Cross‐layer perspective for channel assignment in cognitive radio networks: A survey

SummaryWith the advent of various emerging wireless products, the usage of limited spectrum has grown exponentially in the recent years. In the next few years, that mobile data traffic globally is expected to grow up to 50 EB/month, which is nearly a five times increase over year 2018. Therefore, it will become extremely difficult to satisfy the ever increasing demand through the current fixed spectrum assignment policy in which spectrum band is exclusively used for the particular applications, and it has also led to underutilization of a significant portion of the spectrum (like TV bands). Cognitive radio networks has emerged as a possible solution for the problem which makes dynamic spectrum access possible for unlicensed user when licensed user is not active. Among various operations of cognitive radio, channel assignment to the unlicensed user is very important. Further, wireless regional area network is one of the most important application of cognitive radio, which provides wireless broadband to the rural area using vacant TV channels. This paper discusses channel assignment techniques considering various functionalities for cognitive radio networks in respect of wireless regional area network in the existing literature. Initially, a comprehensive introduction to both cognitive radio networks and wireless regional area networks is provided, and in the end, the paper summarizes the various issues and research challenges in the channel assignment for wireless regional area networks.

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%.

An optimized general target channel sequence for prioritized cognitive radio networks

Cognitive radio networks serve different secondary user applications which have distinct delay requirements. In order to better support the delay-sensitive applications, we consider secondary user traffic to be classified into M prioritized classes based on delay requirements. The priority of a secondary user increases within the same class after each interruption to reduce the cumulative handoff delay. A mixed preemptive/non-preemptive resume priority M/G/1 queueing model is assumed to analyze multiple spectrum handoffs. Closed form expressions are derived for both the extended data delivery time and dropping probability for each secondary user class. The analysis assumes a general target channel sequence, where a secondary user can select either to stay at his current channel or change it after each interruption. This general target channel sequence is optimized using a genetic algorithm in order to minimize the average extended data delivery time of all secondary user classes. Numerical results show that the proposed interruption-based priority mechanism outperforms the existing priority mechanisms in terms of average handoff delay and extended data delivery time in case of changing the target channel while preserves the extended data delivery time in case of always stay. Moreover, the optimized general target channel sequence gives better performance compared to the target channel sequences mentioned in the IEEE 802.22 wireless regional area networks standard for different network cases.

Performance analysis of radio spectrum for cognitive radio wireless networks using discrete time Markov chain

Cognitive radio (CR) arises as an important technique for wireless network with the aim to provide better utilization of radio spectrum, which is being utilized sporadically in some areas. IEEE 802.22 wireless regional area network (WRAN) is the first standard for CR technology designed to opportunistically utilize the unused or under-utilized TV bands. A WRAN cell normally consists of a number of customer premises equipments (CPEs)/CR users and a base station (BS) having master/slave architecture. When a CPE is powered on, it first attempts to associate with the BS. In this paper, a discrete time Markov chain model (DTMC) is presented to show the association process of CPEs with the BS. To the best of our knowledge, this paper is the first in which DTMC Model is analyzed and investigated for WRAN. Using this model, various parameters such as association time, expected return time to the respective backoff stage, first passage time, etc., are derived. Finally, the evaluation results are provided to analyze the system's performance.

Analysis of optimal threshold selection for spectrum sensing in a cognitive radio network: an energy detection approach

The spectrum sensing is a key process of the cognitive radio technology in which the cognitive users identify the unutilized/underutilized primary users (PUs)/licensed users spectrum for its efficient utilization. The sensing performance of cognitive radio (CR) is generally measured in terms of false-alarm probability ( $$ P_{f} $$ ) and detection probability ( $$ P_{d} $$ ). IEEE 802.22 wireless regional area network is one of the typical cognitive radio standards to access unused licensed frequencies of TV band and according to this standard, the false-alarm probability of CR should be ≤ 0.1 and the detection probability must be ≥ 0.9. Further, the detection and false-alarm probabilities are greatly affected by the selected threshold value in the spectrum sensing approach and selection of threshold is a crucial step to yield the status (presence/absence) of PU. In most of the available literatures, the threshold is decided by fixing one parameter ( $$ P_{f} $$ or $$ P_{d} $$ ) and optimizing the other parameter ( $$ P_{d} $$ or $$ P_{f} $$ ). Moreover, at low SNR, while achieving one of the targeted sensing parameter, there is significant degradation in the other sensing parameter. Therefore, in this paper, we are motivated to decide the optimal threshold at low SNR (signal-to-noise ratio) in such a way where we can jointly achieve both sensing matrices ( $$ P_{f} $$ ≤ 0.1 and $$ P_{d} \ge 0.9 $$ ) and provided better sensing performance in comparison to that of the traditional constant false-alarm rate and constant detection rate (CDR) threshold selection approaches. Further, we have illustrated that at low SNR, the proposed optimal threshold selection approach has provided better throughput as compare to that of the threshold selected by traditional CDR approach. The proposed approach has improved throughput approximately 24.63% when compared with CDR at chosen SNR.

QoS-based dynamic channel selection algorithm for cognitive radio based smart grid communication network

Smart Grid (SG) operation requires multi-way communication among power generation, transmission, distribution, and consumer facilities. The complete SG architecture involves multiple layers of networks stretching from energy control center to consumer facilities and multiple applications with diverse Quality-of-Service (QoS) requirements. To meet these requirements, Cognitive Radio (CR) which offers efficient spectrum utilization and sharing, has been considered as a favorable solution. Due to diverse requirements of latency, data rate and reliability, it is a great challenge to support various SG applications under spectrum sensing uncertainties, Signal-to-Noise Ratio (SNR) variations and availability of desired channel bandwidth. In this paper, we propose a dynamic channel selection algorithm based on Fuzzy Inference System (FIS) capable of selecting the most appropriate available idle channel with desired bandwidth, minimum required SNR and probability of miss detection Pmd. The proposed algorithm utilizes various modes of IEEE Standard 802.22, Wireless Regional Area Network (WRAN), at the physical layer. In case of unavailability of idle channels with required SNR and/or Pmd, we propose a novel approach to select the channel with closest possible parameters aiming to reduce the re-transmission probability and thus achieve the desired throughput, latency and reliability requirements. The performance is compared with existing algorithms to demonstrate the effectiveness and superiority of the proposed algorithm.

Subcarriers assignment scheme for multiple secondary users in OFDMA‐based IEEE 802.22 WRAN: A game theoretic approach

AbstractIn this work, cognitive radio and orthogonal frequency division multiple access–based IEEE 802.22 wireless regional area networks is considered. Generally, subchannel is assigned to the user having the best channel gain to that subchannel and problem is known to be NP‐hard. This assignment sometimes results in the unfair allocation where user with best channel gain is allocated more carriers as compared with the user with worst channel condition. In this work, a suboptimal algorithm is developed in which initially optimal number of subcarriers are found considering the equal power distribution. The problem is formulated as an oligopoly market competition and a noncooperative Cournot game is used in which different unlicensed secondary users (SUs) compete for the number of subcarriers based upon the data rate they are getting from current channel condition. The fair distribution of subcarriers is ensured by finding the Nash equilibrium. After subchannels are assigned to the SUs, power allocation is performed for each user with the water‐filling algorithm. Simulation results show that the proposed approach can attain superior performance over considered benchmark scheme in the literature in terms of minimum data rate and fairness achieved by the SU. Results validating fair allocation of subcarriers is also shown.

A Sub-mW Integrating Mixer SAR Spectrum Sensor for Portable Cognitive Radio Applications

A low power mixed-signal integrating mixer successive approximation register (SAR) architecture is proposed for direct spectrum estimation in portable transceivers targeting IEEE 802.22 wireless regional area network cognitive radio applications. The integrating mixer SAR implements the short-time Fourier transform in the analog domain and digitizes its amplitude at the end of the integration period. The architecture consists of an array of folded double balanced mixers connected to a common subset of binary-weighted capacitive loads. Current domain windowing is applied in the first stage followed by mixing, integration and analog-to-digital conversion (ADC) in the second stage. Windowing sets the detection bandwidth and provides flexible low pass filtering while a load capacitor array enables integration with programmable time constant and acts as the sampling capacitors of a SAR ADC. A prototype chip is fabricated in IBM’s $0.13\mu {\text{m}}$ CMOS process. The measured results indicate an average dynamic range of 27.9–25.7 dB over a frequency range of 0.05–1.25 GHz, while consuming 0.88 mW from 1.1/1.2 V supplies.

Optimal On Demand Delay-constrained Fair Distribution for self-coexistence WRAN

Resource allocation plays a critical role in improving the performance of Wireless Regional Area Network (WRAN) in terms of throughput, delay and fairness. In this paper, we fully consider the distinct delay constraints and frame demands of users and formulate the resource allocation optimization problem as an integer programming problem. A new approach termed On Demand Delay-constrained Fair Distribution (ODDFD) is proposed to solve this optimization problem. One distinguished feature of the ODDFD is that it is able to deal with both delay-sensitive networks and delay-insensitive networks. In this manner, ODDFD is able to maximize the fairness of resource distribution both in short term and in long term. In addition, to better assess the fairness problem in resource allocation, we propose a new fairness metric termed priority-dependence Fairness Index (F-Index) to fully consider priority levels of different users. Simulation results verify that the proposed F-Index is applicable in situations with both homogeneous and heterogeneous priorities among users. Extensive simulations are conducted to evaluate the performance of ODDFD. We conclude that, compared to existing approaches, the ODDFD reduces the unexpected delays in frame transmissions in delay-sensitive networks and significantly improves the fairness of resource allocation in delay-insensitive networks.

On the target channel sequence selection for multiple handoffs in cognitive radio-based wireless regional area networks

In cognitive radio networks, handoff occurs when an unlicensed spectrum user has to switch to a new target channel from its current operating channel which a secondary user was using opportunistically. This situation raises whenever either the licensed primary user appears again or the channel's condition get worst. Substantial sensing time can be saved if a secondary user can make a proactive decision about selecting the future vacant target channel to resume the unfinished transmission before starting its transmission. This paper proposes a novel target channel sequence selection scheme for cognitive radio networks, which minimises the estimated service time of a secondary user by reducing the multiple handoffs. A non-iterative algorithm is implemented, which does not require the use of an exhaustive search technique as usual to determine the target channel sequence. Simulation results show that the proposed scheme outperforms both the random scheme and a considered benchmark scheme in terms of service time, cumulative handoff delay and throughput achieved by the secondary user.