Multiple Cognitive Users Research Articles

Joint detection algorithm for multiple cognitive users in spectrum sensing

Spectrum sensing technology is a crucial aspect of modern communication technology, serving as one of the essential techniques for efficiently utilizing scarce information resources in tight frequency bands. This paper first introduces three common logical circuit decision criteria in hard decisions and analyzes their decision rigor. Building upon hard decisions, the paper further introduces a method for multi-user spectrum sensing based on soft decisions. Then the paper simulates the false alarm probability and detection probability curves corresponding to the three criteria. The simulated results of multi-user collaborative sensing indicate that the simulation process significantly reduces false alarm probability and enhances detection probability. This approach effectively detects spectrum resources unoccupied during idle periods, leveraging the concept of time-division multiplexing and rationalizing the redistribution of information resources. The entire computation process relies on the calculation principles of power spectral density in communication theory, involving threshold decision detection for noise power and the sum of noise and signal power. It provides a secondary decision detection, reflecting the perceptual decision performance of logical detection methods with relative accuracy.

Distributed user pairing and effective computation offloading in aerial edge networks

Future Sixth-Generation (6G) mobile communication networks extremely require the global connectivity and the ground Base Stations (BSs) are difficult to develop in some specific areas, such as mountainous areas. Therefore, the aerial networks are the key framework for the future communications, in which the aerial vehicle could act as the access point. Additionally, Mobile Edge Computing (MEC) is also essential to enhance the data processing capabilities of aerial networks. In this paper, we study a comprehensive communication-computation resource management problem for jointly optimizing user pairing, power and time allocation in the MEC aided Cognitive Radio (CR) aerial networks, namely CR-MEC aerial networks. Explicitly, this multilevel optimization problem could be decomposed into the user pairing and power allocation as well as time allocation sub-problems. In the conceived CR-MEC aerial networks, we propose a User Pairing and Computation Offloading Management Algorithm (UPCOMA) based on three-sided matching theory, aiming to minimize the system’s energy consumption. At the first step of UPCOMA, multiple Primary Users (PUs) and Cognitive Users (CUs) on the ground negotiate to each other with the suitable power allocation coefficients and construct the stable user pairs. Moreover, the stable user pairs would match to a high altitude platform who act as the base station, which is for appropriately allocating Transmission Time Slots (TSs) at the second step of UPCOMA. Additionally, a hybrid offloading mode is proposed in our conceived networks in order to support ground users to offload their tasks adaptively according to their individual deadlines. Furthermore, the simulation results reveal that the relative performance of UPCOMA is close to that of the Brute-Force Search Algorithm (BFSA) with low complexity. Meanwhile, the hybrid offloading mode with less energy consumption supports much more ground user pairs to offload tasks compared to the binary mode.

A Channel Allocation Method Considering the Asymmetry of Available Channels for Centralized Underwater Cognitive Acoustic Networks.

Due to the unpredictable presence of Non-Cognitive Users (NCUs) in the time and frequency domains, the number of available channels (i.e., channels where no NCUs exist) and corresponding channel indices per Cognitive User (CU) may differ. In this paper, we propose a heuristic channel allocation method referred to as Enhanced Multi-Round Resource Allocation (EMRRA), which employs the asymmetry of available channels in existing MRRA to randomly allocate a CU to a channel in each round. EMRRA is designed to enhance the overall spectral efficiency and fairness of channel allocation. To do this, the available channel with the lowest redundancy is primarily selected upon allocating a channel to a CU. In addition, when there are multiple CUs with the same allocation priority, the CU with the smallest number of available channels is chosen. We execute extensive simulations in order to investigate the effect of the asymmetry of available channels on CUs and compare the performance of EMRRA to that of MRRA. As a result, in addition to the asymmetry of available channels, it is confirmed that most of the channels are simultaneously available to multiple CUs. Furthermore, EMRRA outperforms MRRA in terms of the channel allocation rate, fairness, and drop rate and has a slightly higher collision rate. In particular, EMRRA can remarkably reduce the drop rate compared to MRRA.

Resource management for traffic imbalance problem in green cognitive radio networks

The main goal of the cognitive radio network (CRN) is to provide high throughput and ubiquitous data access, but now it is focusing on energy-efficient green CRN. The energy consumption of CRN depends upon the total network time of cognitive users (CUs) and the unbalanced traffic load of CUs (when multiple CUs try to approach the same channel and their time and energy are wasted due to congestion). Hence, we design the channel decision models based on queuing priority for two different channel selection strategies, first probability-based channel selection strategy (PCSS) and second sensing-based channel selection strategy (SCSS). This model helps to calculate the optimum channel selection probability in PCSS and the optimum number of channels in the SCSS. With the help of the above-mentioned parameters, the total network time of CUs can be minimized, and their traffic load can be distributed among multiple applicant channels. We have considered the effects of PU’s interruption and sensing errors (missed detection and false alarm) in our analysis. The result shows that, for heavy traffic load of CUs, the sensing-based strategy provides lesser network time, while for low traffic load, the probability-based strategy performs better. Next, we analyze the energy consumption at various operational modes in CRN and propose a channel sensing strategy that represents the energy-saving percentage for different conditions. The proposed strategies can minimize the total network time over 60% and energy consumption over 75% compared to the non-load balancing strategy.

Hybrid NOMA/OMA-Based Dynamic Power Allocation Scheme Using Deep Reinforcement Learning in 5G Networks

Non-orthogonal multiple access (NOMA) is considered a potential technique in fifth-generation (5G). Nevertheless, it is relatively complex when applying NOMA to a massive access scenario. Thus, in this paper, a hybrid NOMA/OMA scheme is considered for uplink wireless transmission systems where multiple cognitive users (CUs) can simultaneously transmit their data to a cognitive base station (CBS). We adopt a user-pairing algorithm in which the CUs are grouped into multiple pairs, and each group is assigned to an orthogonal sub-channel such that each user in a pair applies NOMA to transmit data to the CBS without causing interference with other groups. Subsequently, the signal transmitted by the CUs of each NOMA group can be independently retrieved by using successive interference cancellation (SIC). The CUs are assumed to harvest solar energy to maintain operations. Moreover, joint power and bandwidth allocation is taken into account at the CBS to optimize energy and spectrum efficiency in order to obtain the maximum long-term data rate for the system. To this end, we propose a deep actor-critic reinforcement learning (DACRL) algorithm to respectively model the policy function and value function for the actor and critic of the agent (i.e., the CBS), in which the actor can learn about system dynamics by interacting with the environment. Meanwhile, the critic can evaluate the action taken such that the CBS can optimally assign power and bandwidth to the CUs when the training phase finishes. Numerical results validate the superior performance of the proposed scheme, compared with other conventional schemes.

Energy-Efficiency-Based Power Allocation Scheme in Multi-user Single-DF-Relay Cognitive Networks

Due to the enhancement in both spectral efficiency and energy efficiency, cognitive radio (CR) being combined with relay cooperation technique is deemed as a promising way to realize green-broadband communication in the fifth generation (5G) networks. In this paper, for such CR-relay networks operating in underlay mode, when multiple secondary cognitive users (SUs) share a common cognitive relay in decode-and-forward manner to complete their physical transmissions, system power consumption is investigated. For the scenarios where the co-channel interference to primary users and the peak transmit power of SUs and cognitive relay are constrained, the problem of power allocation in CR-relay network is formulated to minimizing sum-system-consumption. Then, based on the principle that power-consumption minimization is equivalent to energy-efficiency maximization, a novel power allocation scheme is proposed. Further numerical simulation is used to verify the optimality of the proposed power allocation scheme.

Degrees of Freedom for Half-Duplex and Full-Duplex Multi-User Cognitive Radios

The degrees of freedom (DoF) of multi-user cognitive radios (CR) under half-duplex (HD) and full-duplex (FD) are studied in this work. Due to the fact that FD adopted multiple cognitive users (CUs) suffer not only self-interference (SI) and primary-user interference (PUI) but also multi-user interference (MUI) from the other CUs, the DoF metric is constrained by various interference factors and shows scale invariance properties with respect to the temporal, frequency and spatial dimensions. In this regard, the average DoF is characterized in both spatio and temporal dimensions using limitation calculation (LC) and interference alignment (IA) methods, under interweave, underlay, overlay and hybrid CR patterns. Due to the multi-user specified impacts, the achievable DoF of CU is constrained by the maximum transmit power of the other CUs, and the HD and FD tradeoff for multi-user CR is determined by both MUI and time-antenna splitting. Theoretical analysis indicates that the secondary user power and secondary user number only inflict impacts on LC and IA based average DoF respectively. Moreover, because of distributed CR processing, the average DoF for MU CR is upper-bounded by that of single-user CR. Simulation results validate the effects of MUI, SI, PUI and user number on the average DoF. It shows that IA achieves higher DoF than that of LC for multi-user CR, indicating that the DoF loss due to MUI can be reduced if interference mitigation is available.

Hybrid Spectrum Handoff Scheme of Imperfect Sensing in Cognitive Radio Networks

Background: In the actual cognitive radio network, there exist the imperfect sensing such as false alarm and missed detection which can lead to the inaccurate spectrum handoff and cause more uncertain problems. Meanwhile, the predetermined target channel has high risk of being unavailable in the proactive-decision spectrum handoff scheme. Objective: To solve the problem that the state of the predetermined target channel is updated in the proactive-decision spectrum handoff scheme, we present a novel hybrid spectrum handoff scheme based on Preemptive Resume Priority (PRP) M/G/m queuing network model in this paper. Methods: The proposed scheme combines the advantages of proactive-decision spectrum handoff and reactive-decision spectrum handoff, and performs the spectrum sensing during the waiting time of the cognitive user on the target channel. On this basis, we consider the influence of multiple cognitive users, multiple authorization channels, multiple spectrum handoffs and other factors on the spectrum handoff delay of cognitive user. Then, the detailed analysis and derivations of cognitive user’s extended data delivery time are conducted. Furthermore, the effect of imperfect spectrum sensing on the spectrum handoff performance of cognitive users is discussed. Results: Compared with traditional spectrum handoff schemes, numerical results show that the extended data delivery time of the proposed scheme is smaller, and the performance of spectrum handoff is further improved. In addition, the performance of the proposed scheme is less affected by the probability of false alarm and missed detection with frequent channel states variations. Simulation results are given to validate the analytical results. Conclusion: The hybrid spectrum handoff scheme provide better performance on the spectrum sharing between primary users and cognitive users in cognitive radio network under imperfect sensing condition.

Distributed Sequential Coalition Formation Algorithm for Spectrum Allocation in Underlay Cognitive Radio Networks

In this paper, we study the resource allocation problem, including the joint consideration of user grouping and power allocation, of an, underlay cognitive radio (CR) network employing non-orthogonal multiple access (NOMA), which is referred to as the NOMA-CR network. Based on the non-transferable utility coalition formation game theory, the so-called distributed sequential coalition formation (DSCF) algorithm is leveraged to solve the user grouping problem, where multiple cognitive users within a group can access the primary user's spectrum band while satisfying a minimum rate requirement of the primary user. The simulation results show that a near-optimal performance can be achieved by implementing the proposed DSCF as well as the optimal power allocation algorithms. Furthermore, the results validate that NOMA-CR can significantly outperform the traditional orthogonal multiple access CR, in terms of throughput. Finally, it is shown that by applying a novel adaptive trellis turbo coded modulation technique to the underlay NOMA-CR network, a significant throughput gain can be achieved.

Spectrum Sharing With Network Coding for Multiple Cognitive Users

In this paper, an intelligently cooperative communication network with cognitive users is considered, where in a primary system and a secondary system, respectively, a message is communicated to their respective receiver over a packet-based wireless link. The secondary system assists in the transmission of the primary message employing network coding, on the condition of maintaining or improving the primary performance, and is granted limited access to the transmission resources as a reward. The users in both systems exploit their previously received information in encoding and decoding the binary combined packets. Considering the priority of legitimate users, a selective cooperation mechanism is investigated and the system performance based on an optimization problem is analyzed. Both the analytical and numerical results show that the condition for the secondary system accessing the licensed spectrum resource is when the relay link performs better than the direct link of the primary transmission. We also extend the system model into a network with multiple secondary users and propose two relay selection algorithms. Jointly considering the related link qualities, a best relay selection and a best relay group selection algorithm are discussed. Overall, it is found that the throughput performance can be improved with multiple secondary users, especially with more potential users cooperating in the best relay group selection algorithm.

Energy-Aware Multiuser Scheduling for Physical-Layer Security in Energy-Harvesting Underlay Cognitive Radio Systems

In this paper, we consider an energy-harvesting underlay cognitive radio (CR) system, which is comprised of multiple cognitive users (CUs), a common cognitive base station (CBS), and multiple passive eavesdroppers (Es). When CUs transmit to CBS, Es may overhear the confidential transmissions from CUs. In the aforementioned system, all CUs are considered to be equipped with energy harvesters to collect energy from their surrounding environments. Meanwhile, the transmit power of CUs shall be limited by a tolerable interference temperature to guarantee the quality-of-service of a primary user. In order to improve the physical-layer security of energy-harvesting CR systems, we propose an Energy-AwaRe mulTiuser scHeduling (EARTH) scheme, which takes into account both the interference temperature constraint and residual energy level harvested from the ambient surroundings. We consider the use of security-reliability tradeoff (SRT) as a metric to evaluate the performance of proposed EARTH scheme. To be specific, we derive closed-form expressions of outage probability (OP) and intercept probability (IP) for the proposed scheme over Rayleigh fading channels. For the purpose of comparison, the SRT analysis of round-robin scheduling (RRS) and conventional multiuser scheduling (CMUS) methods is also carried out. Numerical results show that the SRT of proposed EARTH scheme is better than that of RRS and CMUS methods, demonstrating the advantage of our proposed scheme against eavesdropping attacks. Additionally, it is illustrated that the sum of IP and OP can be minimized for RRS and CMUS as well as EARTH schemes through a time allocation between the energy harvesting and information transmission phases.

Spectrum Allocation for Cognitive Radio Networks Using the Fireworks Algorithm

The fireworks algorithm features a small number of parameters, remarkable optimization ability, and resistance to a local optimum. Based on the graph coloring model, the fireworks algorithm is introduced for the first time to solve the spectrum allocation problem for cognitive radio networks, thus maximizing utility and fairness of spectrum allocation. Two-layer binary coding is adopted for individual fireworks. The first layer refers to the coding of cognitive users used to determine channels that can be connected with the user. The second layer refers to the auxiliary coding of channels responsible for addressing mutual interference among multiple cognitive users when they connect with the same channel at the same time. Explosion operator, mutation operator, and the selection operation are designed to allocate the spectrum for the cognitive radio network. Simulation results demonstrate superiority and efficiency of the proposed algorithm in terms of spectrum allocation.

Malicious Cognitive User Identification Algorithm in Centralized Spectrum Sensing System

Collaborative spectral sensing can fuse the perceived results of multiple cognitive users, and thus will improve the accuracy of perceived results. However, the multi-source features of the perceived results result in security problems in the system. When there is a high probability of a malicious user attack, the traditional algorithm can correctly identify the malicious users. However, when the probability of attack by malicious users is reduced, it is almost impossible to use the traditional algorithm to correctly distinguish between honest users and malicious users, which greatly reduces the perceived performance. To address the problem above, based on the β function and the feedback iteration mathematical method, this paper proposes a malicious user identification algorithm under multi-channel cooperative conditions (β-MIAMC), which involves comprehensively assessing the cognitive user’s performance on multiple sub-channels to identify the malicious user. Simulation results show under the same attack probability, compared with the traditional algorithm, the β-MIAMC algorithm can more accurately identify the malicious users, reducing the false alarm probability of malicious users by more than 20%. When the attack probability is greater than 7%, the proposed algorithm can identify the malicious users with 100% certainty.

Spectrum allocation and protocol based on cognitive acoustic technique in underwater networks

In this paper, a strategy is developed for spectrum sharing among multiple cognitive users in underwater environment. This strategy requires all nodes to negotiate and reallocate the channels before sending data, and Hungarian method is used to maximize the sharing rewards. Simulation results show that the proposed strategy can avoid collisions between source-destination node pairs, and guarantee that the communication system gets maximum sharing rewards. Both the parameters of POMDP model and the number of available channels have influence on the system sharing rewards, and the rewards will increase when the channels have larger transition probabilities or more channels are available for communication. However, the channels with larger bandwidths can attract more nodes to access, and thus will lead to more collisions.

Energy-Aware Cooperative Wireless Networks With Multiple Cognitive Users

In this paper, we study and analyze cooperative cognitive radio networks with arbitrary number of secondary users (SUs). Each SU is considered a prospective relay for the primary user (PU) besides having its own data transmission demand. We consider a multi-packet transmission framework that allows multiple SUs to transmit simultaneously because of dirty-paper coding. We propose power allocation and scheduling policies that optimize the throughput for both PU and SU with minimum energy expenditure. The performance of the system is evaluated in terms of throughput and delay under different opportunistic relay selection policies. Toward this objective, we present a mathematical framework for deriving stability conditions for all queues in the system. Consequently, the throughput of both primary and secondary links is quantified. Furthermore, a moment generating function approach is employed to derive a closed-form expression for the average delay encountered by the PU packets. Results reveal that we achieve better performance in terms of throughput and delay at lower energy cost as compared with equal power allocation schemes proposed earlier in the literature. Extensive simulations are conducted to validate our theoretical findings.

Cognitive radio intelligent-MAC (CR-i-MAC): channel-diverse contention free approach for spectrum management

Cognitive radio was introduced to fill up the imbalance between spectrum scarcity and spectrum underutilization. So to make such an ideology work, a network which can utilize all the available channel in the best efficient manner, without causing any harmful interface to primary user (PU) and maintaining the Quality of Service (QoS) for cognitive user (CU) is required. In both Mesh as well as ad-hoc networks, effective utilization of the white-spaces by the CUs maintaining the QoS for both primary and CU is a challenging task due to the frequent and instant change in their channel status. In this paper an intelligent-MAC (i-MAC) for cognitive radio (CR) using two transceivers based on hybrid approach of combination of cooperative decision and contention-free approach is proposed. Cooperative decision, to overcome hidden node or the case when there is no common channel between the CU's and contention-free approach, to solve the issues in contention mechanism, where same channel is selected simultaneously by multiple CU's. Proposed CR-i-MAC permits an effective dynamic spectrum access to CUs without effecting the QoS for PU's. The simulative performance analysis of proposed CR-i-MAC is tested in various critical cases like multi-channel single-radio and multi-channel multi-radio over different on demand routing protocols like dynamic source routing, ad-hoc on demand distance vector and weighted cumulative expected transmission time using network simulator (NS-2). The performance of the network is measured on the basis of parameters like throughput, delay and interference. The analysis of the simulation results shows that the proposed CR-i-MAC outperforms various other CR MAC's in terms of both increased throughput and reduced delays thereby making the system stable and efficient.

Malicious Users Detection and Nullifying their Effects on Cooperative Spectrum Sensing

Abstract Submitted：October 27, 2015 1 st Revision：March 20, 2016 Accepted：March 24, 2016* This study was supported by research fund from Chosun University, 2015.** Dept. of Information and Communication Engineering, Chosun Univ.*** Dept. of Information and Communication Engineering, Chosun Univ, Corresponding AuthorSpectrum sensing in cognitive radio (CR) has a great role in or der to utilize idle spectrum opportunistically, since it is responsible for making available dynamic spectrum access efficiently. In this research area, collaboration among multiple cognitive radio users has been proposed for the better ment of detection reliability. Even though cooperation among them improves the spectrum sensing performance, some fals ely reporting malicious users may degrade the performance rigorously. In this article, we have studied the de tection and nullifying the harmful effects of such malicious users by applying some well known outlier detection methods bas ed on Grubb’s test, Boxplot method and Dixon’s test in cooperative spectrum sensing. Initially, the performance of each technique is compared and found that Boxplot method outperforms both Grubb’s and Dixon’s test for the case w here multiple malicious users are present. Secondly, a new algorithm based on reputation and weight is developed to identify malicious users and cancel out their negative impact in final decision making. Simulation results demonstrate that the proposed scheme effectively identifies the malicious users and suppress their harmful effects at the fusio n center to decide whether the spectrum is idle.

Adaptive-TTCM-Aided Near-Instantaneously Adaptive Dynamic Network Coding for Cooperative Cognitive Radio Networks

An adaptive dynamic network coding (ADNC) scheme conceived for cooperative cognitive radio (CCR) is proposed for devising a novel ADNC-CCR system. The system is designed for supporting communications between multiple primary users (PUs) and a common base station (BS), where the independent source information is transmitted from the PUs to the BS with the aid of multiple cognitive users (CUs) acting as relay nodes (RNs). To facilitate the recovery of the source information at the BS, the CUs invoke the ADNC technique, which is assisted by our cooperative protocol operating by exchanging the CCR-based control information between near-instantaneously adaptive turbo trellis coded modulation (ATTCM) and network coding (NC) codec, as well as between the CUs and the BS. More particularly, near-instantaneous ATTCM is employed for appropriately adjusting both the modulation mode and the code rate of the channel coding itself and of the NC, according to the near-instantaneous channel conditions. As a result, our novel ADNC-CCR system constructed on the basis of our holistic approach is capable of providing an increased throughput, despite reducing the transmission period of the PU. This reduced transmission period can also be directly translated into an increased duration for secondary communications of the CUs. In our proposed ADNC-CCR scheme, both the PUs and CUs employ our ATTCM scheme. As an additional novelty, the network encoder may also be activated in its adaptive mode for supporting the CUs, depending on the Boolean value of the feedback flags generated based on the success/failure of the ATTCM decoder and of the network decoder, which is evaluated and fed back by the BS. Quantitatively, it was found that the joint holistic design of our ATTCM-ADNC-CCR scheme is either capable of freeing up an approximately 40% of the PU's bandwidth in comparison to its noncooperative counterpart or increasing the attainable throughput by 2 bits/symbol.

An Intelligent Fuzzy Based Energy Detection Approach for Cooperative Spectrum Sensing

Cognitive radio systems are helpful to access the unused spectrum using the popular technique, referred to as spectrum sensing. Spectrum sensing involves the detection of primary user (PU) signal using dynamic spectrum access. Cooperative spectrum sensing takes advantage of the spatial diversity in multiple cognitive radio user networks to improve the sensing accuracy. Though the cooperative spectrum sensing schemes significantly improve the sensing accuracy, it requires the noise variance and channel state information which may lead to transmission overhead. To overcome the drawbacks in conventional cooperative spectrum sensing, this paper proposes a fuzzy system based cooperative spectrum sensing. Selection combining (SC) and maximum ratio combining (MRC) are used at fuzzy based fusion center to obtain the value of the sensing energy. These energy values are utilized in finding the presence of PU, results in improved sensing accuracy. In addition, an intelligent fuzzy fusion algorithm determines the PU presence without the channel state information based on multiple threshold values. Simulation results show that the proposed scheme outperforms the existing schemes in terms of sensing accuracy.

Secrecy Outage and Diversity Analysis of Cognitive Radio Systems

In this paper, we investigate the physical-layer security of a multi-user multi-eavesdropper cognitive radio system, which is composed of multiple cognitive users (CUs) transmitting to a common cognitive base station (CBS), {while multiple eavesdroppers may collaborate with each other or perform independently in intercepting the CUs-CBS transmissions, which are called the coordinated and uncoordinated eavesdroppers, respectively}. Considering multiple CUs available, we propose the round-robin scheduling as well as the optimal and suboptimal user scheduling schemes for improving the security of CUs-CBS transmissions against eavesdropping attacks. Specifically, the optimal user scheduling is designed by assuming that the channel state information (CSI) of all links from CUs to CBS, to primary user (PU) and to eavesdroppers are available. By contrast, the suboptimal user scheduling only requires the CSI of CUs-CBS links without the PU's and eavesdroppers' CSI. We derive closed-form expressions of the secrecy outage probability of these three scheduling schemes in the presence of {the coordinated and uncoordinated eavesdroppers}. We also carry out the secrecy diversity analysis and show that the round-robin scheduling achieves the diversity order of only one, whereas the optimal and suboptimal scheduling schemes obtain the full secrecy diversity, {no matter whether the eavesdroppers collaborate or not. In addition, numerical secrecy outage results demonstrate that for both the coordinated and uncoordinated eavesdroppers, the optimal user scheduling achieves the best security performance and the round-robin scheduling performs the worst.} Finally, upon increasing the number of CUs, the secrecy outage probabilities of the optimal and suboptimal user scheduling schemes both improve significantly.