Interference Power Constraint Research Articles

Reconfigurable Intelligent Surface-Assisted Secure Communication in Cognitive Radio Systems

A reconfigurable intelligent reflective surface (RIS)-assisted cognitive radio (CR) multiple-input multiple-output (MIMO) secure communication system is considered. In the presence of an eavesdropper, a primary base station (PBS) and a cognitive base station (CBS) equipped with multiple antennas communicate to a primary user (PU) and a secondary user (SU), respectively. In order to maximize the achievable secrecy rate of the system, the secrecy rate maximization problem is first transformed into a secure energy efficiency (SEE) problem using an objective function. Then, the security energy efficiency of the system is maximized by jointly optimizing the transmit beam formation of the base station and the reflected beam formation of the smart reflecting surface under the conditions that the total transmitted power constraint and the interference power constraint are satisfied. To address the difficulty in solving the resulting optimization problem, we apply an algorithm based on alternating optimization and semidefinite relaxation, as well as Dinklbach’s algorithm, to solve the problem. Simulation results show that this method can significantly improve the safety energy efficiency of the system.

Coalitional Game Based Resource Allocation in D2D-Enabled V2V Communication

The joint resource block (RB) allocation and power optimization problem is studied to maximize the sum-rate of the vehicle-to-vehicle (V2V) links in the device-to-device (D2D)-enabled V2V communication system, where one feasible cellular user (FCU) can share its RB with multiple V2V pairs. The problem is first formulated as a nonconvex mixed-integer nonlinear programming (MINLP) problem with constraint of the maximum interference power in the FCU links. Using the game theory, two coalition formation algorithms are proposed to accomplish V2V link partitioning and FCU selection, where the transferable utility functions are introduced to minimize the interference among the V2V links and the FCU links for the optimal RB allocation. The successive convex approximation (SCA) is used to transform the original problem into a convex one and the Lagrangian dual method is further applied to obtain the optimal transmit power of the V2V links. Finally, numerical results demonstrate the efficiency of the proposed resource allocation algorithm in terms of the system sum-rate.

Optimized Design for IRS-Assisted Integrated Sensing and Communication Systems in Clutter Environments

In this paper, we investigate an intelligent reflecting surface (IRS)-assisted integrated sensing and communication (ISAC) system design in a clutter environment. Assisted by an IRS equipped with a uniform planar array (UPA), a multi-antenna base station (BS) is targeted for simultaneously sensing multiple targets in the non-light-of-sight (NLoS) region and communicating with multiple communication users (CUs). We consider the joint IRS-assisted ISAC design in the case with Type-I or Type-II CUs, where each Type-I CU and Type-II CU can and cannot cancel the interference from sensing signals, respectively. Under the perfect communication/sensing channel state information assumption, we aim to maximize the minimum sensing beampattern gain among multiple targets, where the sensing beampattern gain qualifies the achieved illumination signal power at the given location of the target of interest. We jointly optimize the BS’s communication-sensing beamformers and the IRS’s phase shifting matrix, subject to the signal-to-interference-plus-noise ratio (SINR) constraint for each Type-I/Type-II CU, the interference power constraint per clutter, the transmission power constraint at the BS, and the cross-correlation pattern constraint. Due to the design variable coupling, the joint IRS-assisted ISAC design problem is shown to be non-convex in the case with Type-I or Type-II CUs. To circumvent the non-convexity dilemma, we propose semidefinite relaxation (SDR) based alternating optimization algorithms in both cases, for which the computational complexity and convergency behavior are analyzed. In the case with Type-I CUs, we show that the dedicated sensing signal at the BS can help enhance the sensing performance gain. By contrast, the dedicated sensing signal at the BS is not required for the IRS-assisted ISAC designs in the case with Type-II CUs. Numerical results are provided to show that the proposed IRS-assisted ISAC design schemes achieve a significant gain over the existing benchmark schemes.

Maximizing the Sum-Rate of Secondary Cognitive Radio Networks by Jointly Optimizing Beamforming and Energy Harvesting Time

In this paper, we consider an energy harvesting (EH) cooperative cognitive radio network (CCRN) framework, in which the primary network (consisting of a transmitter-receiver pair) shares both energy and spectrum with the secondary network (consisting of two transceivers and multiple amplify-and-forward (AF)-based relays). Since the relays have no power source, they periodically switch between the EH and information transmission (IT) tasks. In particular, we apply a sum-rate maximization strategy to jointly obtain the optimal EH time allocation factor and distributed beamforming coefficients that achieve the best system performance for the secondary network under the individual EH power constraints at relays and an interference power constraint at the primary receiver. Although the formulated optimization problem is non-convex and complicated, we devise an efficient iterative scheme by applying the semi-definite relaxation (SDR) technique followed by the successive upper-bound minimization (SUM) strategy. Our simulation results confirm that the proposed method is spectrally and energy efficient.

Performance Analysis of Dual-Hop AF Cognitive Relay Networks with Best Selection and Interference Constraints

In this paper, a dual-hop underlay cognitive relay network (CRN) with a best-relay selection (BRS) scheme under spectrum-sharing constraints from the primary user (PU) is investigated. The system model in this work consists of one PU, one secondary user (SU) and a few SU relays. Both users exchange the information using a half-duplex mode through amplify-and-forward (AF) SU relays. Moreover, all channels are modelled using the Nakagami-m fading model. In this work, the outage probabilities (OPs) are derived for the proposed system model under several scenarios to investigate the network performance under interference power constraint Ip at the PU receiver. In addition, the impacts of the number of relays and the channel fading severity parameters are investigated as well. Furthermore, the system performance is investigated for several PU locations. The various numerical results are verified using a Monte Carlo simulation. Overall, the obtained results show that several factors such as the number of relays, channel fading severity parameters and PU location have a major impact on the outage performance of the SU. The simulation and analytical results are perfectly matched, confirming the accuracy of the analytical derivations.

Network-Coded Cooperative Systems in Cognitive Radio Networks

We study the performance of a network-coded cooperative (NCC) system in an underlay cognitive radio network (CRN). The primary network (PN) consists of a single transmitter-receiver pair, and the secondary network (SN) is an NCC system with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> users, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> relays, and a single destination. The relays employ decode-and-forward (DF) protocol and use network coding (NC). We study the performance of the SN under two types of power constraints: i) the combined peak interference power constraint on the PN and maximum transmit power constraint at the SN; and ii) the single peak interference power constraint on the PN. For the SN, an exact closed-form expression and an asymptotically tight end-to-end outage probability are derived, and the diversity order and coding gain are quantified. Compared to the existing literature, the proposed CRN NCC has four main distinguishable features: i) it applies to general CRN NCC network settings with an arbitrary number of users and relays; ii) it considers general relay selection mechanism and independent and non-identically distributed (i.n.i.d.) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Nakagami-m$ </tex-math></inline-formula> fading channels; iii) it assumes secondary-to-primary and primary-to-secondary interference links; and iv) it provides a generalization of previous work and includes existing results in the literature as special cases.

Performance evaluation of cognitive relay networks for end user mobile over mixed realistic channels

Cognitive relay network is a spectrum dynamic paradigm that exploits the unused portions of the licensed spectrum. This is based on merging both cooperative relaying techniques and cognitive radio network to achieve spectrum efficiency and enhance the overall system performance. In this paper, the presence of mobile users at the destination node is considered. Here, the end users can navigate at relatively fast vehicular velocities causing dynamic multipath fading and high Doppler shift. which can be fairly modelled using Nakagami- m $m\;$ fading channel (i.e. m < 1 $\;m < 1$ ). In a spectrum scarcity environment, a secondary user must deploy an optimal power allocation policy to get higher transmission rates while the overall interference affecting the primary user (PU) is kept below a certain threshold value. In particular, the outage probability (OP) performance is studied over the mixed Rayleigh and Nakagami-m fading channels for different scenarios and a tight closed-form expressions are derived for the system OP of underlay dual-hop cognitive relay networks with a single amplifiy-and-forward (AF) relay with and without the use of the direct link transmission and selection diversity at the destination with interference power constraints for the primary network over independent and non-identical (i.n.i.d) Rayleigh and Nakagami-m fading channels when m < 1 $m < 1$ based on the statistical characteristics of signal-to-noise ratio. Numerical results are presented to evaluate the impact of the fading parameter, m, the maximum aggregated intrusion constraint, and the locations of the primary users (PUs) on different channel scenarios at high vehicular speeds. Monte Carlo simulations are presented to verify and validate analytical results.

On the Capacity of Gaussian MIMO Channels With Memory

The operational capacity of Gaussian MIMO channels with memory was obtained by Brandenburg and Wyner (1974) under certain mild assumptions on the channel impulse response and its noise covariance matrix, which essentuially require channel memory to be not too strong. This channel was also considered by Tsybakov (2006) and its information capacity was obtained in some cases. It was further conjectured, based on numerical evidence, that these capacities are the same in all cases. This conjecture is proved here. An explicit closed-form expression for the optimal input power spectral density matrix is also given. The obtained result is further extended to the case of joint constraints, including per-antenna and interference power constraints as well as energy harvesting constraints. These results imply the information-theoretic optimality of OFDM-type transmission systems for such channels with memory.

Achievable Rate Maximization for Underlay Spectrum Sharing MIMO System With Intelligent Reflecting Surface

In this letter, the achievable rate maximization problem is considered for intelligent reflecting surface (IRS) assisted multiple-input multiple-output (MIMO) systems in an underlay spectrum sharing scenario, subject to interference power constraints at the primary users. The formulated non-convex optimization problem is challenging to solve due to its non-convexity as well as coupling design variables in the constraints. Different from existing works that are mostly based on alternating optimization (AO), we propose a penalty dual decomposition based gradient projection (PDDGP) algorithm to solve this problem. We also provide a convergence proof and a complexity analysis for the proposed algorithm. We benchmark the proposed algorithm against two known solutions, namely a minimum mean-square error based AO algorithm and an inner approximation method with block coordinate descent. Specifically, the complexity of the proposed algorithm grows <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">linearly</i> with respect to the number of reflecting elements at the IRS, while that of the two benchmark methods grows with the third power of the number of IRS elements. Moreover, numerical results show that the proposed PDDGP algorithm yields considerably higher achievable rate than the benchmark solutions.

Secrecy Performance of Underlay Cognitive Radio Networks With Primary Interference

This work explores the physical layer security of an underlay cognitive radio network (CRN) in the presence of a powerful interferer called a primary transmitter (PT) under peak interference power constraint. Under this scenario, the secondary transmitter (Alice) transmits secret information on a single antenna with the highest signal-to-interference plus noise ratio (SINR) to a legitimate receiver (Bob), and an eavesdropper (Eve) attempts to intercept that information. Depending upon the availability of channel state information (CSI) of the eavesdropper channel, we investigate the secrecy performance of the proposed network in the Rayleigh fading environment for both passive and active eavesdropping scenarios. We obtain analytical expressions for the secrecy outage probability, intercept probability, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula> -outage secrecy capacity in a passive eavesdropping scenario. A complete investigation of the average secrecy capacity (ASC) has been made, and novel expressions for the exact and asymptotic ASC have been obtained for active eavesdropping. Bolstering these results, we also define a high SINR power offset, which quantifies the significance of main system parameters on the ASC explicitly. Further, the effect of outdated CSI of Alice to primary receiver link on the various performance metrics with the concept of interference-outage is also studied.

Joint Video Packet Assignment, Power Control and User Scheduling Over Cognitive Multi-Homing Heterogeneous NOMA Networks

Non-orthogonal multiple access (NOMA)-based cognitive heterogeneous multi-homing networks is a very important scenario in the future wireless networks. In this work, we formulate a joint video packet assignment, power control and user scheduling problem as a mixed integer non-linear programming (MINLP) to maximize the total video transmission quality for cognitive multi-homing heterogeneous NOMA networks, which is subject to the maximum accessed number of secondary users at each subchannel, video encoding characteristics, maximum interference power constraint and total available power constraint. For the joint video packet assignment, power control and user scheduling problem, we divide it into a video packet assignment subproblem, a power control subproblem and a secondary user scheduling subproblem for cognitive multi-homing heterogeneous NOMA networks. Firstly, the secondary user scheduling algorithm is proposed using the greedy method. Then, we utilize successive convex approximation (SCA) method to transform the power control subproblem into a convex programming problem, and an approximated optimal power control algorithm is proposed with the dual decomposition method. Finally, a heuristic video packet assignment algorithm is designed, which utilizes the auction theory. Numerical simulation results demonstrate that the proposed algorithms not only improve the video transmission quality, but also enhance the total throughput of cognitive multi-homing heterogeneous NOMA networks.

Energy Efficient Power Control for Cognitive Multibeam-Satellite Terrestrial Networks With Poisson Distributed Users

With great potential to alleviate spectrum scarcity in the next generation wireless communication, cognitive satellite terrestrial networks (CSTNs) have attracted considerable attention recently. To realize efficient spectrum sharing between satellite and terrestrial networks, in this paper, we propose an energy efficient power control scheme for CSTNs, where a multibeam satellite network acts as the secondary system and the cellular network acts as the primary system. Especially, satellite users and primary base stations are spatially Poisson distributed and the channel state information (CSI) of satellite interference link is assumed to be outdated. We firstly analyze the statistical characteristic of the terrestrial aggregate interference with probabilistic stochastic geometry. On this basis, to guarantee reliable communications for both networks, we formulate the power control scheme as an energy efficiency maximization problem subjected to interference power constraints imposed by terrestrial communications and outage constraints of satellite communications. Further, by employing the Dinkelbach and Lagrange duality method, we solve the nonlinear concave optimization problem and derive the optimal solution of the transmit power. Finally, simulation results demonstrate the validity of the theoretical results, reveal the trade-off between the performance of two networks, present the impacts of aggregate interference on the performance of satellite networks, and show the performance superiority of considering outdated CSI compared with perfect CSI assumption in terms of interference violation probability.

Throughput maximisation for multi‐channel energy harvesting cognitive radio networks with hybrid overlay/underlay transmission

This paper focuses on the issue of joint time and power allocation in multi-channel energy harvesting CR networks (EH-CRNs), where the multi-antenna secondary transmitter (ST) opportunistically accesses the licensed subchannels by a hybrid overlay/underlay transmission approach. To improve spectrum efficiency and energy efficiency of the EH-CRNs, the ST scavenges energy from the radio-frequency signal radiated by the primary transmitter, and exploits the harvested energy for data transmission through subchannels of different states in overlay/underlay mode simultaneously. Moreover, under the interference power constraint, energy constraint, and maximum power constraint, the secondary throughput is improved by optimising the allocation of subchannels, the time scheduling between energy harvesting and data transmission, and the power allocation of the ST among different subchannels. A subchannel allocation scheme with low time complexity is proposed, and the secondary throughput optimisation problem is formulated with respect to the time scheduling and power allocation of the ST. Then it is proved the problem is convex, and the problem is solved by a proposed joint time and power allocation algorithm. Numerical results show that the proposed scheme has an advantage of secondary throughput over the other schemes. Finally, the impacts of key relevant factors on the secondary throughput are explored.

Energy-Efficient Resource Allocation for NOMA-Based Heterogeneous 5G Mine Internet of Things

The Mine Internet of Things (MIoT), as an application paradigm of the IoT in mine environment, realizes the state perception and information interaction by connecting massive smart sensing devices deployed in mine, plays an important role in coal mine production. The fifth-generation (5G) is a key enabling technology to provide an efficient and reliable communication link guarantee for MIoT networks. To meet the increasing demand for huge amounts of data transmission, a NOMA-based heterogeneous MIoT communication system is proposed. In this paper, different types of mine smart devices can occupy the same subchannel resources for data transmission by the NOMA technology, which improves the device access and spectrum utilization of the MIoT system. We aim to maximize the energy efficiency (EE) of all small cell networks via power allocation and subchannel assignment. Under the imperfect channel state information (CSI), a joint power allocation and subchannel assignment iterative algorithm is proposed. Specifically, firstly, by considering the cross-layer interference power constraints, maximum power constraints and QoS constraints, the EE optimization problem is formulated as a mixed integer nonlinear fractional programming problem. Secondly, the uncertain CSI is modeled as an elliptical uncertainty set, and the original problem is transformed into an equivalent convex optimization form by using the Dinkelbach method. Finally, an approximate solution is obtained by using the Lagrangian dual approach. The numerical results validate the effectiveness of the proposed algorithm and significantly show its superior performance as compared with the baseline algorithms.

Optimal precoders and power splitting factors in multiuser multiple‐input multiple‐output cognitive decode‐and‐forward relay systems with wireless energy harvesting

SummaryThis paper considers an underlay cognitive radio (CR) wireless network with the assistance of a two‐hop decode‐and‐forward (DF) relay node. Different from the conventional CR relay networks, in this paper, the relay node using power‐splitting (PS) techniques harvests wireless energy transmitted from the secondary base station (SBS) and, then, uses its harvested energy to forward the received signals to multiple secondary receive users (SRUs). Due to the highly mutual dependence of the transmission strategies at nodes on the system performance, the optimal design of signal processing at transceivers to efficiently handle the interference and energy constraints is crucial. This paper studies the jointly optimal design of the precoders, PS factors to maximize the minimum user rate under the transmit power, harvested energy, and interference power constraints. Owing to the nonlinearly and mutually coupled design matrix variables in both objective function and constraints, the joint design of the precoders and PS factors for the concerned problem is mathematically challenging. To tackle these difficulties, we devise the appropriate surrogate functions to recast the nonconvex optimization problem into the convex one. By using the minorization–maximization framework, an efficient iterative algorithm with provable convergence is developed by solving the convex optimization problem in each iteration. Numerical results are provided to evaluate the achievable user rate performance of the considered system and investigate the effects of the interference power thresholds at the primary receive users and the number of antennas at the SBS and the relay on the minimum achievable user rate.

Two-Stage Adaptive Relay Selection and Power Allocation Strategy for Cooperative CR-NOMA Networks in Underlay Spectrum Sharing

In this paper, we consider a novel cooperative underlay cognitive radio network based on non-orthogonal multiple access (CR-NOMA) with adaptive relay selection and power allocation. In secondary networks, dedicated relay assistance and user assistance are used to achieve communication between the base station and the far (and near) user. Here, a two-stage adaptive relay selection and power allocation strategy is proposed to maximize the achievable data rate of the far user while ensuring the service quality of near user. Furthermore, the closed-form expressions of outage probability of two secondary users are derived, respectively, under interference power constraints, revealing the impact of transmit power, number of relays, interference threshold and target data rate on system outage probability. Numerical results and simulations validate the advantages of the established cooperation and show that the proposed adaptive relay selection and power allocation strategy has better outage performance.

On the Secrecy Capacity of MIMO Wiretap Channels: Convex Reformulation and Efficient Numerical Methods

This paper presents novel numerical approaches to finding the secrecy capacity of the multiple-input multiple-output (MIMO) wiretap channel subject to multiple linear transmit covariance constraints, including sum power constraint, per antenna power constraints and interference power constraint. An analytical solution to this problem is not known and existing numerical solutions suffer from slow convergence rate and/or high per-iteration complexity. Deriving computationally efficient solutions to the secrecy capacity problem is challenging since the secrecy rate is expressed as a difference of convex functions (DC) of the transmit covariance matrix, for which its convexity is only known for some special cases. In this paper we propose two low-complexity methods to compute the secrecy capacity along with a convex reformulation for degraded channels. In the first method we capitalize on the accelerated DC algorithm which requires solving a sequence of convex subproblems, for which we propose an efficient iterative algorithm where each iteration admits a closed-form solution. In the second method, we rely on the concave-convex equivalent reformulation of the secrecy capacity problem which allows us to derive the so-called partial best response algorithm to obtain an optimal solution. Notably, each iteration of the second method can also be done in closed form. The simulation results demonstrate a faster convergence rate of our methods compared to other known solutions. We carry out extensive numerical experiments to evaluate the impact of various parameters on the achieved secrecy capacity.

Joint power allocation and collaborative beamforming for physical layer security in underlay CR NOMA relay systems

In this paper, we investigate the problem of joint power allocation and collaborative beamforming for physical layer security in underlay cognitive radio non-orthogonal multiple access relay systems. We consider two relaying schemes, i.e., amplify-and-forward and decode-and-forward, with the goal of maximizing the secrecy rate for the central user subjective to the transmit power constraint at the source node, individual transmit power constraints at relays, rate requirements at the cognitive users and the interference power constraint at the primary receiver. The optimization problems are nonconvex and hard to solve. We propose an efficient iterative algorithm by the constrained concave–convex procedure to solve the nonconvex optimization problems. For a comparison, we provide another method, namely alternating optimization (AO) algorithm. In addition, simulations are provided to show the superiority of our proposed methods with comparison to the AO algorithm and traditional orthogonal multiple access schemes.

Underlay Cognitive Radio With Instantaneous Interference Constraint: A Secrecy Performance

We examine the secrecy performance of the receive antenna selection scheme in interference-limited underlay cognitive radio network (CRN) where the antenna that results in the highest signal-to-interference ratio at the secondary receiver is chosen to improve the secrecy performance of the secondary transmission. Exact and asymptotic expressions for the secrecy outage probability and intercept probability are derived for an interference-limited scenario over a general fading scenario with the assumption that the channel state information (CSI) on the secondary transmitter (ST)- primary receiver (PR) channel is perfect. However, CSI on the ST-PR channel may be outdated due to the time-varying properties or feedback latency from the PU. If the ST allocates transmission power using this outdated CSI, PR's interference constraint will not be satisfied. Therefore, we investigate the impact of outdated CSI on the secrecy performance of an interference-limited CRN when interference from the primary transmitter to SU exits under peak interference power constraint.

Secure Cognitive Radio Communication via Intelligent Reflecting Surface

In this paper, an intelligent reflecting surface (IRS) assisted spectrum sharing underlay cognitive radio (CR) wiretap channel (WTC) is studied, and we aim at enhancing the secrecy rate of secondary user in this channel subject to total power constraint at secondary transmitter (ST), interference power constraint (IPC) at primary receiver (PR) as well as unit modulus constraint at IRS. Due to extra IPC and eavesdropper (Eve) are considered, all the existing solutions for enhancing secrecy rate of IRS-assisted non-CR WTC as well as enhancing transmission rate in IRS-assisted CR channel without eavesdropper fail in this work. Therefore, we propose new numerical solutions to optimize the secrecy rate of this channel under full primary, secondary users’ channel state information (CSI) and three different cases of Eve’s CSI: full CSI, imperfect CSI with bounded estimation error, and no CSI. To solve the difficult non-convex optimization problem, an efficient alternating optimization (AO) algorithm is proposed to jointly optimize the beamformer at ST and phase shift coefficients at IRS. In particular, when optimizing the phase shift coefficients during each iteration of AO, a Dinkelbach based solution in combination with successive approximation and penalty based solution is proposed under full CSI and a penalty convex-concave procedure solution is proposed under imperfect Eve’s CSI. For no Eve’s CSI case, artificial noise (AN) aided approach is adopted to help enhancing the secrecy rate. Simulation results show that our proposed solutions for the IRS-assisted design greatly enhance the secrecy performance compared with the existing numerical solutions with and without IRS under full and imperfect Eve’s CSI. And positive secrecy rate can be achieved by our proposed AN aided approach given most channel realizations under no Eve’s CSI case so that secure communication also can be guaranteed. All of the proposed AO algorithms are guaranteed to monotonic convergence.