Number Of Cognitive Users Research Articles

Cooperative spectrum sensing algorithm based on cognitive users selection and Adaboost

In cognitive radio networks, it is a challenge to increase the performance of cooperative spectrum sensing when the number of cognitive users become large. In this paper, a novel spectrum sensing algorithm based on the cognitive users selection strategy and Adaboost classification is proposed by adaptively selecting uncorrelated cognitive radio users with the difference of the maximum degree based on the K‐medoids clustering. Since the proposed users selection strategy is based on the correlation evaluation among the cognitive radio users, it is mandatory to have parameters able to measure the correlation among them and divide into distinct clusters. For this, the spatial correlation coefficient and the clustering quality coefficient are proposed to express the correlation characteristics of cognitive radio users in sensing environments. Performance evaluation is conducted through simulations, and the results are shown to the superior detection performance of the proposed CR user selection strategy based on the K‐medoids clustering for cooperative spectrum sensing.

Efficient Spectrum Sharing by Cognitive User Section Through Clustering for D2D Communication

: D2D communication is the direct communication between the wireless network node without the base station's involvement. This direct communication requires spectrum to communicate, which can be leveraged by using a cognitive radio approach through spectrum sharing. Spectrum sharing using sensed free channel among N number of cognitive users is one of the research issues and is an NP-hard problem. This spectrum sharing also called cognitive user selection. Channel sate-based user selection is usually carried. This user selection is carried out in such a way the sum rate in the network will be maximized. Here in this paper, a graph theory-based approach is followed. The entire node-set, which will share the spectrum, is represented as a weighted graph. The interference between the node that shares the spectrum is represented as the edge of the graph, and the participating cognitive user is represented as a node of the graph. Then clustering mechanism is applied to group the node as an interference-free set, and the cognitive user nodes are selected for the share the spectrum. The proposed mechanism simulation result proves that the mechanism can achieve a maximum sum rate.

Dynamic dual threshold cooperative spectrum sensing for cognitive radio under noise power uncertainty

The spectrum sensing performance depends on the accuracy of the detection about whether primary users are busy or idle. Previous studies on cognitive radio spectrum sensing have shown that the cooperation between secondary users can improve their spectrum detection performance in real cognitive networks. Aiming at the problem of threshold mismatch of energy detectors under noise power uncertainty, a cooperative spectrum sensing method with dynamic dual threshold is proposed. Firstly, the utility function is defined with the objective of minimizing the error probability of spectrum sensing, and the optimum threshold of energy detector is derived. Secondly, in order to mitigate the influence derived from noise uncertainty, an effective dynamic dual threshold adjustment mechanism is presented, and the optimizing combinative fusion rule is discussed with the prerequisite of the minimum global error probability. In addition, in view of insufficient number of cognitive users whose sensing results lie in decision zones, the parameter of credibility is defined to choose the secondary users with reliable local detection for final fusion. Simulation results show that our proposed method can mitigate the influence of noise uncertainty and increase the spectrum sensing accuracy compared with other existing methods.

Performance analysis of shadowed-Rice fading channel with cooperative spectrum sensing

ABSTRACTIn this paper, the performance analysis of wireless communication system over shadowed-Rice (SR) composite fading channel has been investigated and analysed. The unified analytical expressions of the average symbol error probability (ASEP) for several coherent and non-coherent modulation schemes separately with different constellation sizes are derived for composite fading channel under two different fade mitigation methods, with maximal ratio combining (MRC) microdiversity (Method 1) and MRC applied over the composite fading channel (Method 2). Furthermore, an asymptotic analysis is carried out and a closed-form expression of the ASEP with Method 2 is presented. Analytical expressions of the corresponding average probability of energy detection (PD) are formulated for both the methods. Finally, the derived PD expression is utilised to analyse the performance of cooperative system assuming erroneous feedback channel. Analysis of optimisation of detection threshold as well as number of cognitive users to minimise the total error rate is also carried out. The closed-form expressions are validated by comparing them with exact numerical results and Monte Carlo simulation.

Spectrum Allocation With Asymmetric Monopoly Model for Multibeam-Based Cognitive Satellite Networks

With the rapid development of modern satellite communications, broadband satellite services are experiencing a period of remarkable growth in both user population and available bandwidth. Efficient spectrum management is required in order to meet the ever-increasing demand for broadband spectrum. In this paper, a spectrum allocation scheme for cognitive satellite networks is proposed to improve spectrum efficiency by addressing the situation that scarce spectrum resource is under-utilized while the overall demands of cognitive satellite users are not satisfied. The proposed scheme is devised to optimize bandwidth efficiency by achieving the Bayesian equilibrium through spectrum competition among cognitive satellite users. Due to the scarcity of spectrum resource, satellite systems have to eliminate some of the cognitive users’ transmission information types in order to fulfill the spectrum needs of priority users. After declining one or several kinds of modulation modes, cognitive users can update their spectrum lists. With the increase in number of cognitive users and their corresponding transmission information types, the complexity of the optimization problem increases significantly and becomes a computation burden to cognitive satellite systems. Therefore, in this paper, we propose a simplified solution for spectrum resource optimization in a computation-efficient manner. Through rounds of eliminating operations, the satellite systems can identify the final Bayesian equilibrium as an optimal spectrum allocation strategy. We also provide proofs for the existence of Bayesian equilibrium. Numerical results are given to evaluate the performance of our proposed method from diverse perspectives.

Low Energy Consumption for Cooperative and Non-cooperative Cognitive Radio

Recently the subject of energy-efficient is very important in cognitive radio (CR), especially during spectrum sensing, since the large energy consumption (EC) cost, produces a restriction in their implementation especially in devices with limited power, i.e battery. In these design, energy detector consumes a significant part of energy during spectrum sensing to detect the activity of the primary user (PU). In this paper, we investigated a method for improving EC in two scenarios: non-cooperative and cooperative. The idea behind the improvement is based on sensing the spectrum with low-density samples. The optimization concept for reducing EC through controlling the number of frequency samples to be sensed is illustrated as well as the probability of detection in both scenarios. To evaluate the proposed method a comparison is made between the proposed method and censoring method. The performance of energy detection system is evaluated in AWGN and Rayleigh fading channels. The simulation results show that in non-cooperative scenario at Eb/No equal 10 dB, and for sensing ratio equal 50%, EC decreases by 50% and 46% with sma loss in of detection probability of 5% in AWGN channel and 12% in Rayleigh channel. In cooperative scenario, the results show that as the number of cognitive users (CU) increased the average EC per user decreased with an improvement in probability of detection. In case of sensing ratio 50%, the EC is decreased by 43.6% as compared with censoring method.

MIMO Cognitive Radio Spectrum Sharing Using Spatial Coding and User Scheduling for Fading Channels

Spectrum scarcity is one of the issue in wireless communication. Dynamic spectrum sharing is the solution for this problem in which the underutilized spectrums are utilized efficiently. Multiple Input Multiple Output (MIMO) based cognitive radio using spatial coding is used to dynamically share the spectrum which allows simultaneous usage of spectrum by more than one user. The drawback of spatial coding is the achievable capacity get reduced with the increased number of cognitive users which limits the number of users to share the spectrum. In order to maximize the number of secondary users sharing the spectrum of the primary user, this paper presents a cluster based multiple primary and secondary user’s MIMO spatial coding which provides higher capacity. The entire network is divided into number of cluster based on the location such that each cluster will be interference free from other. Each cluster is designed with one primary user and many secondary users and a User Scheduling algorithm called Cluster Based Max Signal Power User Scheduling (CBMSPUS) is proposed to select two best secondary users in each cluster. Since the performance of spatial coder depends on the channel matrix, this paper analyze the spatial pre-coder under Rayleigh, Rican and Nakagami fading channels with multiple users and evaluate the capacity of users under CBMSPUS scheduling algorithm. The results show that the Nakagami fading channel achieves high capacity than others. Primary user calculated capacity is 10.8bits/HZ /channel at low SNR region and 14.2 bits/HZ/channel at high SNR region. The secondary user archives maximum capacity of 9.8bits/HZ /channel at low SNR and 13 bits/HZ/channel at high SNR. The Proposed Scheduling method offers maximum of 15dB gain comparing FIFO scheduling algorithm.

Packet Size Optimization for Cognitive Radio Sensor Networks Aided Internet of Things

Cognitive radio sensor networks (CRSNs) is the state-of-the-art communication paradigm for power constrained short range data communication. It is one of the potential technologies adopted for Internet of Things (IoT) and other futuristic machine-to-machine-based applications. Many of these applications are power constrained and delay sensitive. Therefore, CRSN architecture must be coupled with different adaptive and robust communication schemes to take care of the delay and energy efficiency at the same time. Considering the tradeoff that exists in terms of energy efficiency and overhead delay for a given data packet length, it is proposed to transmit the physical layer payload with an optimal packet size (OPS) depending on the network condition. Furthermore, due to the cognitive feature of CRSN architecture overhead energy consumption due to channel sensing and channel handoff plays a critical role. Based on the above premises, in this paper, we propose a heuristic exhaustive search-based Algorithm-1 and a computationally efficient suboptimal low complexity Karuh–Kuhn–Tucker (KKT) condition-based Algorithm-2 to determine the OPS in CRSN architecture using variable rate m-QAM modulation. The proposed algorithms are implemented along with two main cognitive radio assisted channel access strategies based on distributed time slotted-cognitive medium access control (DTS-CMAC) and centralized common control channel-based cognitive medium access control (CC-CMAC) and their performances are compared. The simulation results reveal that proposed Algorithm-2 outperforms Algorithm-1 by a significant margin in terms of its implementation time. For the exhaustive search-based Algorithm-1 the average time consumed to determine OPS for a given number of cognitive users is 1.2 s, while for KKT-based Algorithm-2, it is of the order of 5–10 ms. CC-CMAC with OPS is most efficient in terms of overall energy consumption but incurs more delay as compared to DTS-CMAC with OPS scheme.

Energy‐aware secondary user selection in cognitive sensor networks

In cognitive radio, accurate spectrum sensing is essential to optimally use the available spectrum opportunities. On the other hand, energy is a scarce resource especially in cognitive sensor networks. In this study, the authors combine both these conflicting requirements and propose an energy-aware secondary user selection algorithm for cognitive sensor networks. First, an optimisation problem is solved to obtain the minimum required number of cognitive users, whereas satisfying the system requirements. Second, the most eligible cognitive users are identified through a probability-based approach. They study two extreme cases by focusing on either energy or accuracy parameters. By numerical analysis, it is shown that the accuracy benchmark is increased by as much as 39% by only considering the sensing accuracy, and the energy benchmark is reduced by as low as 76% by only considering the remaining level of energy. In addition, they conduct computer simulation and compare the network's lifetime at several sensing accuracy thresholds. It is elaborated that greater sensing accuracy thresholds lead to longer network lifetime. Finally, the effects of several fusion rules on the proposed method are studied through simulation and numerical analyses. It is discussed that the Majority rule has the best performance among the examined rules.

Capacity analysis of based-regular-topologies cognitive wireless mesh networks with power control

Capacity analysis is a fundamental and essential work for evaluating the performance of cognitive wireless mesh network (CWMN) which is considered a promising option for the future network. Power control is an efficient way to avoid interference and improve capacity of wireless mesh networks. In this paper, a quantitative result of the per-node average throughput capacity of CWMN with power control is deduced for the first time, which is much helpful for understanding the limitations of CWMN. Firstly, under the large-scale channel fading model and protocol interference model, a closed-form expression for the maximum channel capacity of each node with power control is presented, under the constraint that the interference tolerated by the primary users (PUs) does not exceed a threshold. And then, with the deduced channel capacity result, the per-node average throughput capacity of CWMN is derived based on two regular topologies, i.e. square topology and triangle topology. The simulation results indicate that the capacity is effectively improved with power control, and affected by topology, tolerated interference threshold, the number of cognitive users (CUs) and primary users (PUs).

Efficient method for reducing the average control bits in a distributed cooperative sensing in cognitive radio system

In cognitive radio (CR) networks, the incorrect detection of primary users causes inefficient spectrum utilisation and harmful interference to the primary users, so spectrum sensing is an important problem that must be well done. However, multipath fading and path loss effects always reduce the performance of spectrum sensing. Cooperative spectrum sensing improves the sensing performance of cognitive users. However, when the number of cognitive users cooperating with each other is very large, the reporting bits increase and therefore more bandwidth will be needed. In this study, the authors try to reduce the average number of control bits that is exchanged between CR users. The authors consider two different systems: single band detection system and wideband system. The analysis are done for perfect and imperfect control channels. By using a ring-based distributed spectrum sensing model, they propose a method with little required bandwidth to inform the CRs from the final decision about the activity of the primary user. Analytical and numerical results show that this method reduces the average number of control bits and therefore the required control bandwidth. Moreover, the analytical results represent that the imperfect control channels do not affect the performance of the proposed single band system and has a little effect on the performance of our wideband scheme.

Opportunistic Scheduling for Uplink Cognitive Cellular Networks with Outage Protection of the Primary User

This letter advocates a novel opportunistic scheduling strategy for an uplink cognitive cellular network, as considered in [1]. Different from previous proposals, the proposed strategy chooses the cognitive user (CU) with the best instantaneous channel quality in addition to guaranteeing the reliable operation of primary user (PU). For such a strategy, it is analytically shown that in comparison with previous proposals, a greater average rate and a lower average bit error rate (BER) can be achieved. Interestingly, it is manifested that with an increase in the number of CUs, both the average rate and the average BER of the proposed strategy are ameliorated. Moreover, it is indicated that under the same outage protection criterion for the PU, a much lower transmit power is sufficient for the proposed strategy to optimize the system performance especially for a large number of CUs , as compared with previous strategies.

A sequential cooperative spectrum sensing scheme based on cognitive user reputation

The spectrum sensing plays an essential role in Cognitive Radio (CR), which enables opportunistic access to underutilized licensed spectrums. Cooperative spectrum sensing can help improve sensing performance. However, when the number of cognitive users is large, the latency and network traffic for reporting sensing results to the Fusion Center (FC) become extremely large, which may result in an extended sensing time and collision in the control channel between Cognitive Users (CUs) and the FC. In this paper, we propose an extended Sequential Cooperative Spectrum Sensing (SCSS) scheme in which the reputation of individual CU is used to ensure that the FC efficiently collects local sensing data from CUs. The proposed scheme reduces the number of sensing reports required while improving sensing performance in comparison with the conventional SCSS scheme even when few malicious users exist in the network.

Selection of Cognitive Users in Cooperative Spectrum Sensing

Cooperative spectrum sensing under network overhead constraints is studied. To protect the primary user well, the detection probability must exceed the predefined threshold. Based on the protection of the primary user, the constraints on optimal number of cognitive users are defined by weighting the detection performance and the usage efficiency in a target function. The analysis of the target function is given under energy fusion strategy in the fusion center. The simulation results show the validity of the constraints.

Performance Analysis of Uplink Cognitive Cellular Networks with Opportunistic Scheduling

In this letter, we investigate the performance of uplink cognitive cellular networks with opportunistic scheduling with respect to the mean capacity and the average bit error rate (BER) of the scheduled cognitive user (CU). In the considered system, both CUs and the primary user (PU) share the same base station (BS). In contrast to existing CU scheduling schemes, the CU which causes the minimum interference to the PU is selected for transmission. Besides, the transmit power of the selected CU should also satisfy the outage probability requirement of the PU. An interesting observation is that both the mean capacity and the upper bound on the average BER of the scheduled CU are independent of the number of CUs and the transmit power of the PU.

An Efficient Ordered Sequential Cooperative Spectrum Sensing Scheme Based on Evidence Theory in Cognitive Radio

Spectrum sensing is a fundamental function for cognitive radio network to protect transmission of primary system. Cooperative spectrum sensing, which can help increasing sensing performance, is regarded as one of the most promising methods in realizing a reliable cognitive network. In such cooperation system, however the communication resources such as sensing time delay, control channel bandwidth and consumption energy for reporting the cognitive radio node's sensing results to the fusion center may become extremely huge when the number of cognitive users is large. In this paper, we propose an ordered sequential cooperative spectrum sensing scheme in which the local sensing data will be sent according to its reliability order to the fusion center. In proposed scheme, the sequential fusion process is sequentially conducted based on Dempster Shafer theory of evidence's combination of the reported sensing results. Above all, the proposed scheme is highly feasible due to the proposed two ordered sequential reporting methods. From simulation results, it is shown that the proposed technique not only keeps the same sensing performance of non-sequential fusion scheme but also extremely reduces the reporting resource requirements.

Cooperative Sensing in Cognitive Radio Networks-Avoid Non-Perfect Reporting Channel

Problem statement: Cognitive radio is a candidate technology for more efficient spectrum utilization systems based on opportunistic spectrum sharing. However, a common assumption regarding cognitive radios is that they are unlicensed spectrum users that should defer to (avoid interfering with) existing primary sources. Therefore effective sensing of primary users was a major focus of current research. Cooperative spectrum sensing had been proposed to overcome the problem associated with the local sensing node problem-due to noise uncertainty, fading and shadowing. However, reporting the sensing result required perfect channel to avoid degradation in sensing performance due to fading. It also required a large bandwidth assuming large number of cognitive user. Approach: In this study we presented a hard decision auto-correction reporting scheme that directly corrects the errors in the reported bit and further minimizes the average number of reporting bits by allowing only the user with a detection information to report its result. We used analytical formulation to investigate the reporting scheme, by employing such selection technique; the reporting error due to the fading channel was reduced. Results: The sensing performance was investigated and we showed through simulations and probabilistic analysis the sensing performance improvements achieved via the proposed method. Numerical result showed much decrease in reporting bit without affecting the sensing performance.

A Simple MAC Protocol for Cognitive Wireless Networks

A simple distributed Medium Access Control (MAC) protocol for cognitive wireless networks is proposed. It is assumed that the network is slotted, the spectrum is divided into a number of channels, and the primary network statistical aggregate traffic model on each channel is given by independent Bernoulli random variables. The objective of the cognitive MAC is to maximize the exploitation of the channels idle time slots. The cognitive users can achieve this aim by appropriate hopping between the channels at each decision stage. The proposed protocol is based on the rule of least failures that is deployed by each user independently. Using this rule, at each decision stage, a channel with the least number of recorded collisions with the primary and other cognitive users is selected for exploitation. The performance of the proposed protocol for multiple cognitive users is investigated analytically and verified by simulation. It is shown that as the number of users increases the user decision under this protocol comes close to the optimum decision to maximize its own utilization. In addition, to improve opportunity utilization in the case of a large number of cognitive users, an extension to the proposed MAC protocol is presented and evaluated by simulation.