Secondary Base Station Research Articles

Cooperative caching and coordinated beamforming technique for cognitive radio networks

Scarcity of frequency spectrum is one of the main issues in wireless communications. Cognitive radio networks (CRNs) have been considered as an effective way of improving the spectrum efficiency by opportunistically using the spectrum resources through appropriate cooperation between primary and secondary networks. Exploitation of content caching in CRNs can enhance the system performance and reduce the backhaul cost and delay. In this paper, we propose a combined caching strategy and base station coordination in CRNs to achieve a proper balance between the signal cooperation gain and the content diversity gain. Depending on the availability and placement of the requested content, we propose a zero-forcing coordinated beamforming technique to simultaneously transmit the most popular contents that are cached in every secondary base station and achieve the signal cooperation multiplexing gains, also we propose a maximum ratio transmission technique to deliver the less popular contents which are cached in different secondary base stations and achieve the caching diversity gain. Enumeration of the solution space search is used to obtain the optimal cache solution. Numerical results show that our proposed solution outperforms the cooperative caching and transmission solution proposed where only a maximum ratio transmission technique is used.

Performance Analysis of NOMA-Based Underlay Cognitive Radio Networks With Partial Relay Selection

This paper investigates outage and throughput performance of non-orthogonal multiple access (NOMA) based underlay cognitive radio (i.e., CR-NOMA) network under partial relay selection (PRS) scheme. Here NOMA is used in the secondary network, where K half duplex, decode-and-forward (DF) relays are available for assisting the secondary base station (SBS) to deliver information to the secondary users (SUs). We derive analytical expressions for the outage probabilities experienced by the SUs under imperfect successive interference cancellation (i-SIC) conditions. The interference threshold constraint of the primary receiver and the maximum transmit power constraint of the secondary nodes are considered for the analysis. To provide more insights on the outage performance, we obtain expressions for the asymptotic outage probabilities of the SUs in the high transmit power region. Next, we derive analytical expressions for the optimal power allocation (OPA) factors at the SBS and at the selected relay that independently maximize the delay limited throughput of the secondary network in CR-NOMA system. We also determine the jointly optimal power allocation factors that maximize the throughput. We use numerical and simulation investigations to establish that the outage probabilities of the SUs reduce significantly while the throughput improves under the considered PRS scheme, compared to random relay selection and fixed relaying strategies. Further, it is established that the proposed OPA factors can significantly reduce the outage probabilities experienced by the SUs and improve the system throughput compared to equal/random power allocation schemes.

Deep Q-learning-based resource allocation for solar-powered users in cognitive radio networks

Abstract This paper considers uplink solar-powered cognitive radio networks (CRNs) where multiple secondary users (SUs) transmit data to a secondary base station (SBS) by sharing a licensed channel of a primary system. A deep Q-learning (DQL) algorithm, which combines non-orthogonal multiple access (NOMA) and time division multiple access (TDMA) techniques, is proposed to maximize the long-term throughput of the system. By using our scheme, the agent (i.e. the SBS) can obtain the optimal decision by interacting with the environment to learn about system dynamics. Simulation results validate the superiority of the performance under the proposed scheme, compared with traditional schemes.

Relay selection and power allocation for secrecy sum rate maximization in underlying cognitive radio with cooperative relaying NOMA

Cooperative communication that integrates cognitive radio and non-orthogonal multiple access is recognized as an emerging technology for fifth-generation and beyond wireless networks. However, security is still a critical issue because of the risk that confidential information will be overheard in wireless transmission environments. Thus, physical-layer security appears as a powerful alternative to complement, or even replace, the traditional use of encryption-based approaches. In this paper, we investigate a particle swarm optimization-based power allocation and relay-selection scheme to enhance physical-layer security by maximizing the secrecy sum-rate in a cooperative relaying cognitive radio-non-orthogonal multiple access system. First, we formulate the optimization problem subject to the constraints of minimum data rate at each secondary user and maximum transmission power at the secondary base station and the relay, provided that the interference induced by the base station and the relay on the primary users’ receivers is below an acceptable level. Afterward, we describe the cooperative relaying cognitive radio-orthogonal multiple access system to compare the secrecy sum-rate performance of the proposed system with that of the orthogonal multiple access baseline scheme. Satisfactorily, simulation results show that by applying the non-orthogonal multiple access transmission strategy, our proposed scheme reaches higher secrecy sum-rate than the baseline scheme.

A New Primary Protection Method With Received Power-Based 3D Antenna Rotation Range Prediction for Dynamic Spectrum Access

We propose a new primary protection method for Dynamic Spectrum Access (DSA), in which a secondary system uses a frequency band assigned to a primary system. Following a DSA implementation plan in Japan, we take care of a practical scenario where a primary system's transmission station (PTS) moves along a predefined course or area, and a corresponding primary reception station (PRS) keeps its antenna boresight facing towards the moving PTS. For accurate interference calculation from the secondary to the primary systems in this scenario, the proposed method takes the movement of the PTS into account and predicts a range of angle variation of the PRS's antenna boresight based on received signal powers from the PTS to the PRS. We conducted computer simulations in three different practical scenarios to demonstrate the effectiveness of the proposed method. The simulation results show that the proposed method can increase the number of available secondary base stations (SBSs) by up to 1.93 times compared to a conventional method.

Joint Power Allocation and Power Splitting for MISO-RSMA Cognitive Radio Systems With SWIPT and Information Decoder Users

In this article, we investigate the rate-splitting multiple access (RSMA) framework in a multiuser multiple-input single-output (MISO) underlay cognitive radio system with power-splitting secondary users and information secondary users by using simultaneous wireless information and power transfer. The RSMA framework is a novel multiple access method based on linearly precoded rate splitting at the secondary base station, and successive interference cancellation at the secondary receivers, which has shown better performance compared with the traditional space-division multiple access (SDMA) method. In particular, the objective is to minimize the transmit power at the secondary base station subject to the constraints of minimum energy harvesting, minimum data rate, and a maximum power level for allowable interference with the primary users. The challenging problem under consideration is nonconvex, and the solution relies on dividing it into outer and inner optimization problems. Then, we propose a particle-swarm-optimization-based algorithm to solve the outer problem, with the inner problem managed by the semidefinite relaxation method. In addition, we present a comparative scheme based on the successive convex approximation method and a scheme based on SDMA. Finally, simulation results confirm the superior performance of the proposed approach in comparison with the other schemes.

Resource Allocation and Trajectory Design in UAV-Assisted Jamming Wideband Cognitive Radio Networks

The secure performance of wideband cognitive radio networks (CRNs) with OFDMA (orthogonal frequency-division multiple access) achieved by using physical layer security is low due to the severe channel fading and the limit transmit power of the secondary base station (SBS). To improve the secure performance, an unmanned aerial vehicle (UAV) assisted jamming wideband CRNs is studied where a UAV transmits the jamming signal to interfere with the eavesdropper (Eve) and the SBS provides communication services for the secondary users (SUs) over multiple sub-carrier channels. The total average secrecy rate of the secondary network is maximized by jointly optimizing the sub-carrier allocation, the jamming UAV trajectory, and the transmission power of the UAV and the SBS. An alternative algorithm is proposed to solve the challenging non-convex optimization problem. Simulation results verify the efficiency of our proposed algorithm and show that UAV-assisted jamming is beneficial for improving secure performance of wideband CRNs. It is also shown that our proposed scheme outperforms the benchmark schemes in terms of the total average secrecy rate.

Joint Resource Allocation and Transmission Mode Selection Using a POMDP-Based Hybrid Half-Duplex/Full-Duplex Scheme for Secrecy Rate Maximization in Multi-Channel Cognitive Radio Networks

Physical layer wireless communications are more and more essential, and are vulnerable to malicious users owing to the nature of broadcast channels. Herein, we consider a centralized multi-channel cognitive radio network in the presence of eavesdroppers (EVEs). In the network, the secondary base station (SBS) shares currently free primary channels to simultaneously communicate with secondary users (SUs), while passive eavesdroppers attempt to overhear data in the secondary communications. Each limited-battery SU is equipped with two antennas (one for transmitting signals, and other for receiving signals) and is powered by a solar energy harvester. Meanwhile, the SBS equipped with multiple antennas can operate in full-duplex (FD) transmission mode (simultaneously transmit and receive signals) or in half-duplex (HD) transmission mode (transmit and receive signals in turn during each half of a time slot) with the SUs. In this paper, we propose a novel scheme to maximize the secondary system security of the multi-channel cognitive system in the presence of multiple passive EVEs, in which the EVEs are able to overhear the data of the SBS-SU transmissions on all the primary channels. The problem of decision making is formulated as the framework of a partially observable Markov decision process (POMDP), and an optimal solution is achieved by adopting value iteration-based dynamic programming. Specifically, in each time slot, the SBS allocates optimal channel and optimal action (i.e. either stay silent or employ HD/FD transmission modes with optimal transmission power) for each SU in order to obtain maximum long-term secrecy rate for the secondary system.

Resource allocation solution for sensor networks using improved chaotic firefly algorithm in IoT environment

Aiming at the problem that the location of the secondary base station affects the interference between the primary and secondary systems directly and the reasonable allocation of channel resources, an Internet of Things (IoT) sensor network resource allocation scheme using an improved chaotic firefly algorithm is proposed. This solution builds a multi-objective optimization model based on interference analysis of the working scenario of the cognitive radio. The goal is to protect the primary user’s normal activity to maximize the throughput of the secondary system and maximize the number of users that can be covered by the secondary base station. Because the multi-objective model is a non-linear convex optimization problem, the paper uses an improved chaotic firefly algorithm to solve it. Chaos algorithm is introduced into the firefly algorithm. By perturbing individuals, the convergence speed is accelerated and the probability of local optimization is reduced. The algorithm can efficiently obtain the optimal solution while reducing the complexity of the problem. The simulation results show that the method proposed in this paper can optimize the performance of the secondary system while guaranteeing the priority of the primary user. And it is superior to several advanced algorithms.

Smart collaborative video caching for energy efficiency in cognitive Content Centric Networks

Due to the prosperity of online media, caching video content has become an important measure to improve the user experience and alleviate the link burden in wireless caching networks. However, facing to perceptual requirements of video users, Scalable Video Coding (SVC) technique has been cumulatively utilized in wireless caching networks, which can guarantee acceptable video quality. In this paper, we propose a smart collaborative video caching policy to boost energy efficiency (EE) in Cognitive Content Centric networking (C-CCN), where the spectrum sharing characteristic of cognitive ratio (CR) is integrated into CCN. With consideration of the imperfect channel-state information (CSI), the collision interference exists between the primary users (PUs) and secondary base stations (SBs). Inspired by this, we derive the expressions of successful content delivery rate (SCDR) and total power consumption for the proposed policy. By using these expressions, the optimal EE model under the caching size constraint is formulated as an optimal content placement problem, which can be solved by the standard gradient projection method. Numerical and simulation results show the efficacy and superiority of the proposed policy compared with some traditional caching schemes.

Error Performance of NOMA-Based Cognitive Radio Networks With Partial Relay Selection and Interference Power Constraints

Non-orthogonal multiple access (NOMA)-based cognitive radio (CR) networks have recently emerged as a promising solution to enhance the spectral efficiency and massive connectivity problems. In this paper, we investigate the error rate performance of relay-assisted NOMA with partial relay selection in an underlay cognitive radio network. In this setup, $K$ relays are used to assist in transmission between secondary NOMA users and a secondary base station (SBS), where the relay (R) with the strongest link with the SBS is selected to amplify-and-forward (AF) its received signals to the secondary receivers. We derive an accurate approximation for the pairwise error probability (PEP) of the secondary users with imperfect successive interference cancellation (SIC). Subsequently, the derived PEP expression is utilized to deduce a union bound, which is considered as an upper bound on the bit error rate (BER). We further formulate an optimization problem to calculate the optimum power coefficients that minimize the derived union bound. Numerical and Monte Carlo simulation results are presented to corroborate the derived analytical expressions and give some useful insights into the error rate performance of each user.

Secure MISO Cognitive-Based Mobile Edge Computing With Wireless Power Transfer

The finite battery capacity, limited spectrum resource and the transmission security are three challenges in designing mobile edge computing (MEC) systems. In this paper, a framework for wireless powered secure multiple-input single-output (MISO) cognitive-based MEC-enabled networks is proposed, which integrates several technologies: physical-layer security, cooperative relaying, cognitive radio (CR), wireless power transfer (WPT) and MEC. Two optimization problems are formulated to maximize the number of computation bits (NCB) of the mobile device (MD) and minimize the total transmission power (TTP) of the primary transmitter (PT) and the SBS, respectively. The formulated problems are non-convex and hard to solve. Two two-phase methods with block coordinate decent (BCD) and Lagrangian dual decomposition methods are proposed to jointly design the beamforming vector of the PT, beamforming matrix of the secondary base station (SBS), the central processing unit (CPU) frequency, the transmit power, the number of the offloaded bits and the offloading time of the MD. Simulation results are presented to show the effectiveness of the proposed methods.

Robust Secure Wireless Powered MISO Cognitive Mobile Edge Computing

Wireless power transfer (WPT) and cognitive radio (CR) are two promising techniques in designing mobile-edge computing (MEC) systems. In this paper, we study a robust secure wireless powered multiple-input single-output (MISO) cognitive MEC system, which integrates several techniques: physical-layer security, WPT, CR, underlay spectrum sharing and MEC. Three optimization problems are formulated to minimize the total transmission power (TTP) of the primary transmitter (PT) and the secondary base station (SBS) under perfect channel state information (CSI) model, bounded CSI error model and the probabilistic CSI error model, respectively. The formulated problems are nonconvex and hard to solve. Three two-phase iterative optimization algorithms combined with Lagrangian dual, semidefinite relaxation (SDR), S-Procedure and Bernstein-type inequalities are proposed to jointly optimize the beamforming vectors of the PT and the SBS, the central processing unit (CPU) frequency and the transmit power of the MD. Simulation results are provided to verify the effectiveness of the proposed algorithms.

A PHY Layer Security Analysis of Uplink Cooperative Jamming-Based Underlay CRNs With Multi-Eavesdroppers

In this paper, the physical layer security of a dual-hop underlay uplink cognitive radio network is investigated over Nakagami- ${m}$ fading channels. Specifically, multiple secondary sources $(S_{i})_{1\leq i \leq N}$ are taking turns in accessing the licensed spectrum of the primary users and communicating with a multi-antenna secondary base station ( ${D}$ ) through the aid of a multi-antenna relay ${R}$ in the presence of ${M}$ eavesdroppers $(E_{k})_{1\leq k \leq M}$ that are also equipped with multiple antennas. Among the remaining nodes, one jammer is randomly selected to transmit an artificial noise to disrupt all the eavesdroppers that are attempting to intercept the communication of the legitimate links, i.e., $S_{i}$ - ${R}$ and ${R}$ - ${D}$ . The received signals at each node are combined using maximum-ratio combining. Secrecy analysis is provided by deriving closed-form and asymptotic expressions for the secrecy outage probability. The impact of several key parameters on the system’s secrecy, e.g., transmit power of the sources, number of eavesdroppers, maximum tolerated interference power, and the number of diversity branches is investigated. Importantly, by considering two scenarios, namely (i) absence and (ii) presence of a friendly jammer, new insights are obtained for the considered communication system. Especially, we tend to answer to the following question: Can better secrecy be achieved without jamming by considering a single antenna at eavesdroppers and multiple-ones at the legitimate users (i.e., relay and end-user) rather than sending permanently an artificial noise and considering that both the relay and the destination are equipped with a single antenna, while multiple antennas are used by the eavesdroppers? The obtained results are corroborated through Monte Carlo simulation and show that the system’s security can be enhanced by adjusting the aforementioned parameters.

Cache-enabled in cooperative cognitive radio networks for transmission performance

The proliferation of mobile devices that support the acceleration of data services (especially smartphones) has resulted in a dramatic increase in mobile traffic. Mobile data also increased exponentially, already exceeding the throughput of the backhaul. To improve spectrum utilization and increase mobile network traffic, in combination with content caching, we study the cooperation between primary and secondary networks via content caching. We consider that the secondary base station assists the primary user by pre-caching some popular primary contents. Thus, the secondary base station can obtain more licensed bandwidth to serve its own user. We mainly focus on the time delay from the backhaul link to the secondary base station. First, in terms of the content caching and the transmission strategies, we provide a cooperation scheme to maximize the secondary user's effective data transmission rates under the constraint of the primary users target rate. Then, we investigate the impact of the caching allocation and prove that the formulated problem is a concave problem with regard to the caching capacity allocation for any given power allocation. Furthermore, we obtain the joint caching and power allocation by an effective bisection search algorithm. Finally, our results show that the content caching cooperation scheme can achieve significant performance gain for the primary and secondary systems over the traditional two-hop relay cooperation without caching.

Distributed NOMA-Based Multi-Armed Bandit Approach for Channel Access in Cognitive Radio Networks

Usually, multiple secondary users (SUs) utilize the opportunistic spectrum access (OSA) in cognitive radio networks to communicate with the secondary base station (sBS). In uplink transmission, each SU can only select one channel from ${C}$ primary channels to sense, access, and transmit data packets with the constraints of hardware and energy. Distributed non-orthogonal multiple access-based multi-armed bandit (D-NOMA-MAB) approach is proposed to solve the problem of the channel selection and the power level selection, which alleviates the impact of the collision in the same channel. D-NOMA-MAB approach improves the energy efficiency of the system and the successful transmission probability obviously by introducing 2-D selection for the arms and the factor of energy efficiency in the policy index of the restless MAB problem.

Contract Theory Based Medium Access Contention Resolution in TDMA Cognitive Radio Networks

Time-division-multiple-access-based cognitive radio networks allow each licensed primary user to transmit its packets exclusively. The available idle slots present an opportunity to the unlicensed secondary users (SUs) to access the licensed channel for their own transmission. The different SUs contending to access the channel during idle time slot may result in collisions and unfair allocation of the channel. To overcome such a situation, this paper proposes a contract theory based bargaining approach to resolve access contention among SUs in a centralized manner. Contract theory is an incentive design mechanism where participants are offered appropriately designed reward to encourage cooperation. To achieve this, the interaction between the secondary base station (BS) and SU is modeled as a labor market using contract theory. First, the ideal case of SUs is examined where the private information of the SUs is completely known to the BS. Next, the practical case of incomplete information is considered where the BS has no private information of the SUs. The preferences of an SU to access the channel is categorized into a finite number of type using the framework of contract-theory. Further, the overall service time of an SU is also analyzed. The simulation results show that the contract can effectively incentivize SU's cooperation, and outperforms the considered benchmark scheme in terms of SU's overall throughput and average service time.

A Contract Theory Approach-Based Scheme to Encourage Secondary Users for Cooperative Sensing in Cognitive Radio Networks

In cognitive radio networks, the identification of a primary user (PU) with the help of spectrum sensing is very important for a secondary user (SU), such that interference free transmission can be performed. In recent times, the cooperative spectrum sensing that improves the reliability of the decisions made about the presence of a PU and overcoming hidden terminal problem by obtaining sensing results from different sensors is gaining much attention. However, the selfish SUs are sometimes not willing to cooperate. This paper proposes a contract theory-based approach, which is an incentive design mechanism where the participants are offered appropriately designed reward to encourage cooperation. The secondary base-station (BS)–SU interaction is modeled as a labor market using contract theory. Contract theory helps in analyzing the case of incomplete information where the BS is not aware of the SU’s private information. Further, the contract is formed in such a way that only the limited number of noncorrelated SUs can participate in sensing such that unnecessary energy consumption is reduced. Simulation results show that the contract can effectively incentivize SU’s cooperation, and outperforms the considered benchmark scheme in terms of PU detection probability.

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.

The Security–Reliability Tradeoff of Multiuser Scheduling-Aided Energy Harvesting Cognitive Radio Networks

We study the physical-layer security of a cognitive radio system in the face of multiple eavesdroppers (EDs), which is composed of a secondary base station (SBS), multiple secondary users (SUs) as well as a pair of primary transmitter (PT) and primary receiver (PR), where the SUs first harvest energy from their received radio frequency signals transmitted by the PT and then communicate with the SBS relying on opportunistic scheduling. We consider two specific user scheduling schemes, namely, the channel-aware user scheduling (CaUS) and the energy-aware user scheduling (EaUS). In the CaUS scheme, an SU having the best instantaneous SU-SBS link (spanning from SUs to SBS) will be activated to communicate with the SBS. By contrast, the EaUS scheme takes into account both the amount of energy harvested from the PT and the instantaneous quality of the SU-SBS link. We analyze the security–reliability tradeoff (SRT) of both the CaUS and EaUS schemes in terms of their intercept versus outage probability. We also provide the SRT analysis of traditional round-robin user scheduling (RrUS) used as a benchmarker of the CaUS and EaUS schemes. We demonstrate that the EaUS scheme achieves the best outage and secrecy performance in the high main-to-eavesdropper ratio (MER) region, but a worse secrecy performance than the CaUS method in the low-MER region. Moreover, from a security versus reliability perspective, the CaUS outperforms both the EaUS and the RrUS in the low-MER region. Surprisingly, this also implies that although the user scheduling criterion of EaUS exploits the knowledge of both the amount of harvested power and instantaneous channel state information (CSI), it exhibits a degraded physical-layer security in the low-MER region due to the fact that the increased harvested energy is beneficial not only for the legitimate SBS receiver but also for the EDs.