On energy efficient secure routing in multi-hop underlay D2D communications for IoT applications

Integrating visible light communication (VLC) with the reconfigurable intelligent surface (RIS) significantly enhances physical layer security by enabling precise directional signal control and dynamic adaptation to the communication environment. These capabilities strengthen the confidentiality and security of VLC systems. This paper presents a comprehensive study on the joint optimization of VLC access point (AP) power allocation, RIS association, and RIS elements orientation angles for secure VLC systems, while considering rate-splitting multiple access (RSMA) and power-domain non-orthogonal multiple access (NOMA) schemes. Specifically, two frameworks are proposed to maximize both the minimum secrecy rate (SR) and the minimum secrecy energy efficiency (SEE) by jointly optimizing power allocation, RIS association, and RIS elements orientation angles for both power-domain NOMA and RSMA-based VLC systems. The proposed frameworks consider random device orientation and guarantee the minimum user-rate requirement. The proposed optimization frameworks belong to the class of mixed integer nonlinear programming, which has no known feasible solution methodology to guarantee the optimal solution. Moreover, the increased degree of freedom and flexibility from the joint consideration of power control, RIS association and element orientation results in a large set of decision variables and constraints, which further complicates the optimization problem. To that end, we utilize a genetic algorithm-based solution method, which through its exploration and exploitation capabilities can obtain a good quality solution. Additionally, comprehensive simulations show that the RSMA scheme outperforms the power-domain NOMA scheme across both the SR and SEE metrics over various network parameters. Furthermore, useful insights on the impact of minimum user rate requirement, number of RIS elements, and maximum VLC AP transmit power on the minimum SR and SEE performances are provided.

Dynamic spectrum access has been proposed to address the spectrum scarcity. Based on this access mode, secondary users are allowed to opportunistically operate when primary users are absent. Secondary Users are, however, required to relinquish the spectrum upon return of the incumbent spectrum holder. Although it improves spectrum utility, opportunistic spectrum access limits secondary users' access to exogenous spectrum holes vacated by primary users. We argue that spectrum holes should be endogenous, enabled by incentives to incumbent users to increase spectrum availability, while mitigating risk. To this end, we take a different perspective on dynamic spectrum sharing and propose a coopetive framework, whereby primary and secondary users engage in a cooperative, yet competitive, auction-driven spectrum sharing to enhance spectrum usage. In this framework, the primary users'spectrum is organized in three bands, namely exclusive usage, usage right and management right bands. Based on this structure, spectrum is traded as financial options to increase trading flexibility and capture the value primary and secondary users attach to spectrum access and usage. Spectrum trading between primary and secondary users is formalized as a utility maximization problem. Approximate solutions to this problem are derived and their performance is analyzed. The results show that spectrum trading, which combines revocable and exclusive leasing, provides higher utilities for both primary and secondary users.

We investigate opportunistic cooperation between secondary (unlicensed) users and primary (licensed) users in cognitive radio networks. We consider two models for such cooperation. In the first model, called the Cooperative Relay Model, a secondary user cannot transmit its own data concurrently with a primary user. However, it can employ cooperative relaying in order to improve the effective transmission rate of the primary user. In the second model, called the Interference Model, a secondary user is allowed to transmit its data concurrently with a primary user. However, the secondary user can “cooperate” by deferring its transmissions when the primary user is busy. In both models, the secondary users must make intelligent cooperation decisions as they seek to maximize their own throughput subject to average power constraints. The decision options are different during idle and busy periods of the primary user, and the decisions in turn influence the durations of these periods according to a controllable infinite state Markov chain. Such problems can be formulated as constrained Markov decision problems, and conventional solution techniques require either extensive knowledge of the system dynamics or learning based approaches that suffer from large convergence times. However, using a generalized Lyapunov optimization technique, we design a novel greedy and online control algorithm that overcomes these challenges. Remarkably, this algorithm does not require any knowledge of the network arrival rates and is provably optimal.

We consider a cooperation scenario between primary users and untrusted secondary users in cognitive radio networks. The secondary users are willing to help the primary users to relay the primary users' messages in reward for being allowed to share the primary users' spectrum bands. However, the primary users might be reluctant to accept this help, since the secondary users are untrustworthy and may try unauthorized decoding of the primary users' messages. This paper will answer the question: when is this cooperation mutually beneficial for primary and secondary users? Taking an approach of information-theoretic secrecy, such as coding techniques for wiretap channels, the primary users can allow the secondary users to sense and relay the message, while ensuring that the secondary users are ignorant of the primary users' messages. We characterize an achievable secrecy rate of primary users with a rate of the secondary users' communication. From the derived rate pairs, an optimization problem is formulated such that the secondary transmitter distributes its transmit power to maximize its data rate while providing a higher secrecy rate to the primary users. We demonstrate that this cooperation can provide a positive secrecy rate, even when a non-cooperative scheme achieves a zero secrecy rate.

Cognitive radio methodologies have the potential to dramatically increase the throughput of wireless systems. Herein, control strategies which enable the superposition in time and frequency of primary and secondary user transmissions are explored in contrast to more traditional sensing approaches which only allow the secondary user to transmit when the primary user is idle. In this paper, the optimal transmission policy for the secondary user when the primary user adopts a retransmission-based error control scheme is investigated. The policy aims to maximize the secondary users' throughput, with a constraint on the throughput loss and failure probability of the primary user. Due to the constraint, the optimal policy is randomized, and determines how often the secondary user transmits according to the retransmission state of the packet being served by the primary user. The resulting optimal strategy of the secondary user is proven to have a unique structure. In particular, the optimal throughput is achieved by the secondary user by concentrating its transmission, and thus its interference to the primary user, in the first transmissions of a primary user packet. The rather simple framework considered in this paper highlights two fundamental aspects of cognitive networks that have not been covered so far: 1) the networking mechanisms implemented by the primary users (error control by means of retransmissions in the considered model) react to secondary users' activity; 2) if networking mechanisms are considered, then their state must be taken into account when optimizing secondary users' strategy, i.e., a strategy based on a binary active/idle perception of the primary users' state is suboptimal.

We address secure communications over energy-harvesting based OFDMA cooperative cognitive radio networks, where one primary user (PU) cooperates with several secondary users (SUs) in terms of both information transmission and energy harvesting. To improve spectrum utilization and ensure that SU transmitters can harvest as much energy as possible, we suppose that SUs are equipped with orthogonally dual-polarized antennas. Based on these setting-ups, we propose the polarization-enabled two-phase cooperative framework, where SU transmitters first apply power splitting technique to harvest energy from radio frequency signals radiated by the PU transmitter, and then use the harvested energy to concurrently transmit their own and the PU's data. Under the proposed framework, we develop the secure resource allocation schemes for the scenarios when SU receivers are untrusted users, implying that each SU receiver may overhear the PU's and the other SUs' confidential information. For this scenario, which has hardly been studied, we investigate the joint allocation of relays, subcarriers, power splitting ratios, and powers, with the objective to maximize the total secrecy rate of all SUs while guaranteeing the PU's minimum secrecy rate. Finally, we validate and evaluate our proposed cooperative framework and resource allocation schemes through numerical analyses.

In cognitive radio networks, secondary users need to access the licensed spectrum while neither disturbing the transmissions of the primary users nor introducing much interference to other secondary users. Hence, proper power controlling is of paramount importance to ensure efficient system operation. The previous work on power control in cognitive networks mainly focuses on the interactions among a set of secondary users. The primary users' influence is rarely considered. In this paper, a new power control game model is formulated, by including the primary users into the player set of the game. The primary users are rewarded for sharing their licensed spectrum with secondary users by setting a reasonable interference cap for the secondary transmissions. However, we ensure a minimum required Quality of Service (QoS) for primary users by severely penalizing their utility if their required transmission quality is not met. Simultaneously, the secondary users achieve energy efficient transmissions while not introducing much interference to both the primary and other secondary users. We prove that the proposed cognitive power control game has a unique Nash equilibrium (NE). The numerical examples show that the proposed game theoretical power control algorithm can provide the secondary users with energy efficient transmissions and the primary users with reasonable monetary rewards, while not compromising their required QoS.

Although cognitive radio technology improves efficiency of spectrum utilization, primary users usually do not gain from opening up the spectrum in the opportunistic spectrum access, and sometimes even suffer from collisions due to secondary users' imperfect spectrum sensing. However, in this paper, we show that if information secrecy is a concern, primary users could actually be better off by allowing secondary users to cooperatively share the spectrum. Specifically, we propose a new cooperation paradigm in cognitive radio networks that primary users improve secrecy with the help of trustworthy secondary users, in the presence of an intelligent and passive eavesdropper attempting to decode primary users' messages. After deriving the achievable pair of primary users' secrecy rate and secondary users' transmission rate under various circumstances, we model the interaction between primary users and secondary users as a Stackelberg game in which transmission power levels are the key to maximize data rates. Moreover, based on a 2-D representation of how achievable rates depend on power-level regions, we apply equilibrium analysis to understand the optimal strategy of primary and secondary users. Finally, simulation results are presented to verify the performance.

The cooperation among the secondary users or among the secondary users and the primary users have proven to bring many benefits to both primary and secondary users in cognitive radio networks. In this paper, cooperative relaying in cognitive radio networks is studied for rateless coding error-control mechanism. For a pair of primary transmitter and receiver, we find the region in which any secondary or cognitive user can cooperate with the primary user in a constructive way. A queueing theoretical model is employed to describe the underlying system parameters and to create a mathematical framework for the analysis. The throughput performance of the secondary users is maximized based on the input traffic of the primary users. Using the unique properties of rateless codes, a low-complexity relay selection mechanism is also introduced. Through the experimental analysis, we show that the proposed rateless-coding-based cooperative mechanism can perform similar to the more complicated and more costly selective-repeat automatic repeat request algorithm. The numerical analysis using the Rapid Analysis of Queueing Systems (RAQS) software package is provided to support the findings.

In a cognitive radio ad hoc network (CRAHN), the secondary user node has a restricted range for sensing other users within the network. To enhance the performance of nodes (secondary and primary users) in a CRAHN, the problem of limited channel sensing range and interference should be reduced which would enable the simultaneous transmission of primary and secondary users. In this paper, a cooperative MAC (medium access control) protocol is proposed—MLCP, which exploits the concept of multichannel network, for obtaining high system throughput. The main purpose of the proposed protocol is to introduce cooperation among secondary users, using the common control channel. The presence of the primary user is detected and the information is shared among neighbouring secondary users within the network proactively. This protocol is simulated using Network Simulator 2 and analysed with respect to system throughput, packet delivery ratio, and end-to-end delay experienced by primary users. The performance of the proposed protocol is also compared with existing cooperative MAC protocol and non-cooperative MAC protocol network scenario.

In this paper, we investigate the power allocation of primary base station (PBS) and cognitive base station (CBS) across different orthogonal frequency division multiplexing (OFDM) subcarriers for energy-efficient secure downlink communication in OFDM-based cognitive radio networks (CRNs) with the existence of an eavesdropper having multiple antennas. For the sake of defending against eavesdropping, artificial noise is used to confuse the eavesdropper at the cost of extra power consumption. For the purpose of improving the energy efficiency (EE) of secure communications, we propose a secrecy energy efficiency maximization (SEEM) scheme by exploiting the instantaneous channel state information (ICSI) of the eavesdropper, called ICSI-based SEEM (ICSI-SEEM) scheme with a given total transmit power budget for different OFDM subcarriers of both PBS and CBS while guaranteeing a certain secrecy rate (SR) for a cognitive user, where a primary user's SR is also taken into consideration for limiting the interference in CRNs at each subcarrier. As for the case when the eavesdropper's ICSI is unknown, we also propose an SEEM scheme by using the statistical CSI (SCSI) of the eavesdropper, namely SCSI-based SEEM (SCSI-SEEM) scheme. Since the ICSI-SEEM and SCSI-SEEM problems are fractional and non-convex, we first transform them into equivalent subtractive problems, and then achieve approximate convex problems by employing the difference of two-convex functions approximation method. Finally, new two-tier power allocation algorithms are proposed to achieve $\varepsilon$-optimal solutions of our formulated ICSI-SEEM and SCSI-SEEM problems. Simulation results illustrate that the ICSI-SEEM has a better secrecy energy efficiency (SEE) performance than SCSI-SEEM, and moreover, the proposed ICSI-SEEM and SCSI-SEEM schemes outperform conventional SR maximization and EE maximization approaches in terms of their SEE performance.

In this article, we investigate optimal beamforming at a multiantenna primary base station (PBS) and a multiantenna cognitive base station (CBS) for energy-efficient (EE) secure downlink communication in cognitive radio networks with one single-antenna primary user (PU), one single-antenna cognitive user (CU), and multiple single-antenna eavesdropping nodes. An artificial noise transmission scheme is used by CBS to protect the data against the eavesdropping security attacks at the cost of extra power consumption. To improve the secrecy energy efficiency (SEE), we propose a SEE maximization (SEEM) scheme by exploiting the instantaneous channel state information (CSI) of the eavesdroppers under the secrecy rate (SR) constraints of the PBS-PU and CBS-CU channels, the quality-of-service requirement of the PU, and the transmit power constraint of the CBS. When the eavesdropping links' instantaneous CSI are unknown at the legitimate transmitters (i.e., PBS and CBS), we propose another SEEM scheme based on the statistical CSI of the eavesdropping links. Since the formulated optimization problems with fractional objective functions are nonconvex and mathematically intractable, we first transform them into equivalent subtractive problems, and then, employ the difference of two-convex functions approximation method to arrive at approximate convex problems. In addition, new two-tier optimal BF algorithms are proposed. Finally, simulation results are presented to illustrate the effectiveness and performance gains of our proposed SEEM schemes over conventional SR-only maximization and EE-only maximization schemes.

The spectrum scarcity problem can be tackled by promoting a more efficient use of the radio spectrum. Spectrum sharing techniques like TV White Spaces (TVWS), Licensed Shared Access (LSA), and Spectrum Access System (SAS), are adequate solutions for this problem and there exist already regulation and standardization efforts worldwide. To evaluate the coexistence between primary and secondary spectrum users, a Long Term Evolution (LTE) multi-cell simulator has been designed, which employs a generic spectrum sharing technique, Dynamic Spectrum Access (DSA), in order to obtain additional network capacity. As a way to bring attention and confidence of the telecommunications sector regarding the benefits that this technology may bring, the analysis is done in terms of interference suffered by incumbents (primary users) and capacity by secondary users. Results have confirmed the unfeasibility of co-channel coexistence for moderate distances between the cordless camera service (incumbent) and LTE network (secondary user) due to high interference. However, for adjacent bands, a gain of 40% in the secondary users’ capacity is possible following more restrictive interference protection requirements and 30% gain with the smaller frequency separation between primary and secondary operating frequencies.

As the novel and effective approach to improving the utilization of the precious radio spectrum, cognitive radio technology is the key to realize the dynamic spectrum access (DSA) networks, where the secondary (unlicensed) users can opportunistically utilize the unused licensed spectrum in a way that confines the level of interference to the range the primary (licensed) users can tolerate. However, there are many new challenges associated with cognitive-radio-based DSA networks, such as the multi-channel hidden terminal problem and the fact that the time-varying channel availability differs for different secondary users, in the medium access control (MAC) layer. To overcome these challenges, we propose an efficient Cognitive Radio-EnAbled Multi-channel MAC (CREAM-MAC) protocol, which integrates the cooperative sequential spectrum sensing at physical layer and the packet scheduling at MAC layer, over the wireless DSA networks. Under the proposed CREAM-MAC protocol, each secondary user is equipped with a cognitive radio-enabled transceiver and multiple channel sensors. Our cooperative sequential spectrum sensing scheme improves the accuracy of spectrum sensing and further protects the primary users. The proposed CREAM-MAC enables the secondary users to best utilize the unused frequency spectrum while avoiding the collisions among secondary users and between secondary users and primary users. We develop the Markov chain model and M/GY/1 queueing model to rigorously study our proposed CREAM-MAC protocol for both the saturation networks and the non-saturation networks. We also conduct extensive simulations to validate our developed protocol and analytical models.

Spectrum sensing ranks amongst cognitive radio's most critical and demanding activities. For radio resource networks to use idle licensed bandwidth, secondary users need to identify the primary user's signal precisely. Cognitive radio networks (CRNs) have been proposed to improve the efficiency of spectrum use to meet the increasing demand for wireless bandwidth; they allow channel communication between secondary (unlicensed) and primary (licensed) users without interruption. A secondary user in a CRN must at all times track the presence of a primary user's signal to prevent the primary user (PU) from attempting to intervene whether the statistical variance of the PU data traffic would boost the prediction outcome provided by multiple current teaching algorithms in estimating the PU's average OFF time and the need for the best adaptive learning to predict accurate PU activities. The objective of the work has been modeled to identify the PUs signal. First, the data has been created via quadrature phase shift keying modulation and quadrature amplitude modulation by convolutional neural network (CNN). A dataset with different orthogonal frequency‐division (OFDM) multiple access signals is generated. Then cyclo‐stationary functions are extracted using the accumulation process fast Fourier Transform. This research aims to use glow worm swarm optimization (GWSO) to automatically check for the optimal design of CNNs without any manual work being required. Also, k‐Nearest Neighbors (kNN) replaces Softmax, as it outperforms conventional CNN architectures with noisy signals. A comparison of the proposed classifier with another machine learning classifier, namely support vector machine, Decision tree (DT), clearly shows that SVM and DT are outperformed by the improved convolution neural network‐glow worm swarm optimization (ICNN‐GWSO) classification. Results of simulation show that the improved scheme outperforms conventional spectrum sensing systems, both in fading and non‐fading settings, where efficiency is measured using measures such as chance, the total likelihood of error, and the ability to optimize data transfer possibilities.