Total Power Constraint Research Articles

Joint Device Assignment and Power Allocation in Multihoming Heterogeneous Multicarrier NOMA Networks

To improve the radio throughput, novel radio access techniques need to be designed. With exploiting the multiuser diversity at power domain, nonorthogonal multiple access (NOMA) is one promising candidate technique for sixth-generation (6G). In this article, a downlink joint device assignment and power allocation problem is investigated in multihoming heterogeneous multicarrier NOMA networks. The joint device assignment and power allocation problem maximizes the network throughput with total power constraint at each base station, required minimum transmission rate for each device, and maximum number of accessed devices at each subchannel. Since the joint device assignment and power allocation problem is a mixed-integer nonlinear problem, the original optimization problem is divided into a device assignment subproblem and a power allocation subproblem. Then, the greedy method is applied to propose a device assignment algorithm, and successive convex approximation theory is adopted to design a power allocation algorithm. Finally, an iterative joint device assignment and power allocation algorithm is proposed. Numerical simulation results demonstrate that the proposed algorithm can improve the throughput and the average satisfactory of devices compared with other algorithms significantly.

Backscatter Communication Powered By Selective Relaying

In this paper, we exploit the cooperative transmission as a new energy supply to support backscatter communication (BackCom), where there are multiple decode-and-forward (DF) relays and only one relay is selected in the cooperative system. The tag circuit power and signal backscattering are respectively supported by transmit powers of the source and the relay, and the minimum mean square error (MMSE) detector is employed at the receiver of the BackCom user to mitigate the interference from the cooperative system. Our objective is to maximize the quality of service (QoS) of the BackCom user which satisfying the QoS of the cooperative system, the total power constraint on the cooperative system and the harvested power constraint on the BackCom user. The probability of feasibility conditions, and optimized joint relay selection and power allocation are investigated in closed-form expressions. The zero forcing (ZF) detection and its comparison with the MMSE detection in the considered system are also analyzed. Simulation results demonstrate the benefit of the proposed scheme compared with traditional ones.

A Dynamic Beamforming Technique for Ultraviolet-Based Indoor Communications

This paper presents a novel dynamic transmit beamforming technique for ultraviolet (UV) based indoor communications. The proposed system is able to estimate the user position and orientation on real time basis. The objective of the proposed scheme is to maximize the signal-to-noise ratio (SNR) at the user location, subject to the total power constraint from all the UV sources. This constraint is essential to satisfy the UV radiation safety exposure limit. We develop an algorithm which first estimates the user location and then utilizes a fraction of the total transmitting power to be directed towards the estimated user location to establish a communication link. We maximize the achievable rate for a line-of-sight (LOS) communication link using the dynamic beamforming technique incorporated with localization in UV indoor communications. It is demonstrated through simulations that the proposed scheme is capable of providing a high received signal-to-noise ratio (SNR) at the desired user location.

Robust Secure Beamforming Design for Two-User Downlink MISO Rate-Splitting Systems

In this paper, we consider max-min fairness for a downlink two-user multi-input single-output (MISO) system with imperfect channel state information available at transmitter (CSIT) taking into account the total power constraint and the physical layer security. Considering the worst-case channel uncertainty for a potential eavesdropper (PE), we study the robust secure beamforming algorithm design which maximizes the minimum achieved worst-case secrecy rate among single-antenna legitimate users. In contrast to existing schemes adopted in the literatures, we propose a rather unorthodox rate splitting (RS) scheme which advocates the dual use of a common message serving both as a desired message and artificial noise (AN) for legitimate users and the PE, respectively. The algorithm design is formulated as a non-convex optimization problem which is generally intractable. As a compromise approach, we apply the successive convex approximation (SCA) method which facilitates the design of a low-complexity suboptimal iterative algorithm. In each iteration, a rank-constrained semi-definite program (SDP) is solved optimally by SDP relaxation (SDR). Simulation results demonstrate that our proposed robust secure beamforming scheme in the MISO-RS secure transmission system outperforms that of the non-robust counterpart. Moreover, our results also unveil that the proposed RS scheme can achieve a superior performance compared to the existing non-orthogonal multiple access (NOMA) schemes and the traditional scheme.

New process optimization framework for laser assisted tape winding of composite pressure vessels: Controlling the unsteady bonding temperature

This paper presents an effective process optimization methodology for laser assisted tape winding (LATW) of complex part geometries by means of a numerical optical-thermal model. A winding path on the cylindrical and ellipsoidal (dome) part of a pressure vessel is considered with varying tooling curvature. First, the process model output is verified with the literature data based on the laser intensity distribution. Then, the transient laser irradiation and temperature distributions on the tape and substrate are described comprehensively. It is shown that the maximum laser intensity increases approximately by 80% and the process (bonding) temperature changes by 80 °C at the intersection of the cylindrical and dome section of the pressure vessel. In order to keep the transient process temperature constant, a robust optimization scheme is utilized by means of a genetic algorithm. The design variable is determined as the total laser power and temperature constraints are defined. The proposed optimization methodology regulates the temperature within 1.5 °C variation with respect to the desired value. In order to compensate the transient local curvature effects on the process temperature, the total laser power varies approximately between 30% and 175% of the reference (non-optimized) case.

Physical Layer Security Designs for 5G NOMA Systems With a Stronger Near-End Internal Eavesdropper

Serial interference cancellation (SIC) technology is the key to ensure a higher system capacity for NOMA. However, SIC may also introduce some critical security risks, since it requires near-end users (NU) demodulate far-end users’ (FU) signals and make the cancellations. It is hard to obtain positive secrecy rate in the presence of a stronger NU eavesdropper. To this end, this paper studies the security designs for a 5G NOMA system with a stronger NU internal eavesdropper. We first consider the two-user case and then extend our results to a multi-user case. After adjusting the order of SIC and employing a cooperative jammer, an optimal power allocation problem is built subject to users’ data rate and total power constraints. The global closed-form optimal solution is achieved for the two-user case, while a closed-form sub-optimal solution is obtained for the multi-user case. For better insight, the jamming gain is introduced to approximately measure the performance gain achieved. Simulation results show that positive secrecy rate is obtained while the users’ data rate are guaranteed.

Enhanced Secrecy Performance of Multihop IoT Networks With Cooperative Hybrid-Duplex Jamming

As the number of connected devices is exponentially increasing, security in Internet of Things (IoT) networks presents a major challenge. Accordingly, in this work we investigate the secrecy performance of multihop IoT networks assuming that each node is equipped with only two antennas, and can operate in both Half-Duplex (HD) and Full-Duplex (FD) modes. Moreover, we propose an FD Cooperative Jamming (CJ) scheme to provide higher security against randomly located eavesdroppers, where each information symbol is protected with two jamming signals by its two neighbouring nodes, one of which is the FD receiver. We demonstrate that under a total power constraint, the proposed FD-CJ scheme significantly outperforms the conventional FD Single Jamming (FD-SJ) approach, where only the receiving node acts as a jammer, especially when the number of hops is larger than two. Moreover, when the Channel State Information (CSI) is available at the transmitter, and transmit beamforming is applied, our results demonstrate that at low Signal-to-Noise Ratio (SNR), higher secrecy performance is obtained if the receiving node operates in HD and allocates both antennas for data reception, leaving only a single jammer active; while at high SNR, a significant secrecy enhancement can be achieved with FD jamming. Our proposed FD-CJ scheme is found to demonstrate a great resilience over multihop networks, as only a marginal performance loss is experienced as the number of hops increases. For each case, an integral closed-form expression is derived for the secrecy outage probability, and verified by Monte Carlo simulations.

Multiuser Full-Duplex IoT Networks With Wireless-Powered Relaying: Performance Analysis and Energy Efficiency Optimization

This paper considers an Internet-of-Things (IoT) network where a multi-antenna access point (AP) and several single-antenna IoT devices (IoDs), operating under the full-duplex (FD) mode, communicate with each other bidirectionally through the help of a wireless-powered FD relay. In particular, the power splitting (PS) protocol is adopted at the amplify-and-forward (AF) relay to implement a simultaneous wireless information and power transfer (SWIPT) receiver. For such a multiuser FD-IoT network assisted by a wireless-powered two-way relay, we derive exact overall outage probability (OOP) expressions and tight closed-form expressions for the ergodic sum rate (ESR) under generalized Nakagami-m fading channels. Furthermore, aiming to maximize the energy efficiency (EE), we obtain optimal power allocation (OPA) under the total power and rate threshold constraints. Finally, extensive numerical and simulation results are presented to corroborate our analytical findings.

Robust and Secure Beamforming for Intelligent Reflecting Surface Aided mmWave MISO Systems

In this letter, we investigate the robust and secure beamforming (RSBF) in an intelligent reflecting surface (IRS) aided millimeter wave (mmWave) multiple input single output (MISO) system, where multiple single antenna eavesdroppers (Eves) are arbitrarily distributed nearby the legitimate receiver (Bob). Considering the channel state information (CSI) of cascaded wiretap channels is imperfectly known at the legitimate transmitter (Alice), the RSBF design problems to maximize the worst case of achievable secrecy rate (ASR) are formulated under the total transmission power and unit-modulus constraints. Since the problems are difficult to solve optimally due to their non-convexity and coupled variables, we substitute the wiretap channels by a weighted combination of discrete samples and propose a RSBF scheme based on alternating optimization and semidefinite relaxation (SDR) techniques, for both colluding and noncolluding eavesdropping scenarios. Simulation results show that the proposed RSBF scheme can effectively improve the ASR and also outperforms other benchmark schemes.

Secure Beamforming for Multiple Intelligent Reflecting Surfaces Aided mmWave Systems

In this letter, secure beamforming in a multiple intelligent reflecting surfaces (IRSs)-aided millimeter-wave (mmWave) system is investigated. In this system, the secrecy rate is maximized by controlling the on-off status of each IRS as well as optimizing the phase shift matrix of the IRSs. This problem is posed as a joint optimization problem of transmit beamforming and IRS control, whose goal is to maximize the secrecy rate under the total transmission power and unit-modulus constraints. The problem is difficult to solve optimally due to the nonconvexity of constraint conditions and coupled variables. To deal with this problem, we propose an alternating optimization (AO)-based algorithm based on successive convex approximation (SCA) and manifold optimization (MO) technologies. Numerical simulations show that the proposed AO-based algorithm can effectively improve the secrecy rate and outperforms traditional single IRS-aided scheme.

Intelligent Reflecting Surface-Assisted Secure Multi-Input Single-Output Cognitive Radio Transmission.

Intelligent reflecting surface (IRS) is a very promising technology for the development of beyond 5G or 6G wireless communications due to its low complexity, intelligence, and green energy-efficient properties. In this paper, we combined IRS with physical layer security (PLS) to solve the security issue of cognitive radio (CR) networks. Specifically, an IRS-assisted multi-input single-output (MISO) CR wiretap channel was studied. To maximize the secrecy rate of secondary users subject to a total power constraint (TPC) for the transmitter and interference power constraint (IPC) for a single antenna primary receiver (PR) in this channel, an alternating optimization (AO) algorithm is proposed to jointly optimize the transmit covariance R at transmitter and phase shift coefficient Q at IRS by fixing the other as constant. When Q is fixed, R is globally optimized by equivalently transforming the quasi-convex sub-problem to convex one. When R is fixed, bisection search in combination with minorization–maximization (MM) algorithm was applied to optimize Q from the non-convex fractional programming sub-problem. During each iteration of MM, another bisection search algorithm is proposed, which is able to find the global optimal closed-form solution of Q given the initial point from the previous iteration of MM. The convergence of the proposed algorithm is analyzed, and an extension of applying this algorithm to multi-antenna PR case is discussed. Simulations have shown that our proposed IRS-assisted design greatly enhances the secondary user’s secrecy rate compared to existing methods without IRS. Even when IPC is active, the secrecy rate returned by our algorithm increases with transmit power as if there is no IPC at all.

Fairness-Aware Throughput Maximization Over Cognitive Heterogeneous NOMA Networks for Industrial Cognitive IoT

In this work, an uplink secondary Internet of Things (IoT) device scheduling and power allocation problem based on imperfect channel state information (CSI) and imperfect spectrum sensing is investigated for industrial cognitive IoT over cognitive heterogeneous non-orthogonal multiple access (NOMA) networks. The joint secondary IoT device scheduling and power allocation problem maximizes the network throughput subject to total power constraint at each secondary IoT device, proportional fairness transmission rate among different secondary IoT devices, maximum number of accessed secondary IoT devices for each subchannel, and interference power threshold constraint at each primary base station (BS). Firstly, successive convex approximation method is adopted to transform the original resource allocation problem into a bi-convex programming problem. Then, we employ the dual decomposition method to analyze the secondary IoT device scheduling criterion and obtain the power allocation close-form expression. Finally, a joint power allocation and secondary IoT device scheduling algorithm with the proportional fairness criterion is proposed. Numerical simulation results demonstrate that the throughput and fairness for the proposed algorithm are better than that of other resource allocation algorithm significantly.

Adaptive bit and power allocation for dual mode index modulation based OFDM system

Orthogonal frequency division multiplexing (OFDM) along with index modulation (IM) is a promising technique for wide applications that can enhance the spectral efficiency (SE) and simultaneously able to mitigate the harmful effects of dispersive wireless channels. The IM technique utilizes an additional dimension to transmit information in terms of determining whether the OFDM subcarrier is active or inactive. In OFDM-IM system, only active subcarriers carry the modulated data symbol while inactive subcarriers remain empty. The concept of dual-mode (DM) OFDM-IM has been proposed to increase the SE with data transmission through inactive subcarriers employing different constellation alphabets with the same modulation order. In DM-OFDM-IM, all the symbols are modulated with a fixed modulation scheme which provides a constant SE over all the channel conditions. In adaptive DM-OFDM-IM, the modulation order for each subblock of OFDM subcarriers is decided according to the instantaneous received signal to noise ratio (SNR) to improve the bit error rate (BER) performance for enhanced SE. In this work, an idea of simultaneous adaptive bit and power loading (BPL) in DM-OFDM-IM system has been provided in which the information bits and power are allocated for each subblock satisfying both target BER of the system and the total transmission power constraints. The numerical results illustrate that adaptive BPL based DM-OFDM-IM system provides a significant gain in SE for the same BER performance as compared to the conventional DM-OFDM-IM system.

Energy Efficient Beamforming Schemes for Satellite-Aerial-Terrestrial Networks

In this paper, we investigate energy efficient transmission for a satellite-aerial-terrestrial network (SATN), where a multi-antenna unmanned aerial vehicle (UAV) is employed as a relay to assist the satellite signal delivery. By considering total power constraint (TPC) or per-antenna power constraint (PPC) at the UAV, we first formulate an optimization problem to maximize the energy efficiency of the SATN, which is defined as ratio of the ergodic capacity to the total power consumption for communication at UAV. Then, by jointly exploiting array signal processing with the Dinkelbach's method, two new beamforming (BF) schemes, namely, TPC-BF and PPC-BF are proposed to solve the non-convex energy efficiency maximization problem. The main advantage of our method is that only angular information-based channel state information is used to obtain BF weight vectors so that a low implementation complexity is achieved. Furthermore, by assuming that the satellite-UAV link undergoes correlated Shadowed-Rician fading while the UAV-terminal link experiences correlated Rician fading, closed-form expressions for the statistics of the equivalent output signal-to-noise ratio are derived and, thus energy efficiency for the considered SATN with BF schemes is analytically presented. Finally, simulation results corroborate the derived expressions and confirm the effectiveness of the proposed BF schemes.

Supply-Power-Constrained Cable Capacity Maximization Using Multi-Layer Neural Networks

We experimentally solve the problem of maximizing capacity under a total supply power constraint in a massively parallel submarine cable context, i.e., for a spatially uncoupled system in which fiber Kerr nonlinearity is not a dominant limitation. By using multi-layer neural networks trained with extensive measurement data acquired from a 12-span 744-km optical fiber link as an accurate digital twin of the true optical system, we experimentally maximize fiber capacity with respect to the transmit signal's spectral power distribution based on a gradient-descent algorithm. By observing convergence to approximately the same maximum capacity and power distribution for almost arbitrary initial conditions, we conjecture that the capacity surface is a concave function of the transmit signal power distribution. We then demonstrate that eliminating gain flattening filters (GFFs) from the optical amplifiers results in substantial capacity gains per Watt of electrical supply power compared to a conventional system that contains GFFs.

Energy Efficiency of Distributed Antenna Systems with D2D Communications under Imperfect CSI

In this paper, we investigate the distributed antenna systems (DAS) based on device to device (DAS-DID) communications under the imperfect channel state information (CSI). Our aim is to maximize the energy efficiency (EE) of the D2D users equipment (DUE) under the constraints of the maximum transmission power of D2D pairs and the quality of service (QoS) requirements of the cellular user equipment (CUE). The worst-case design is considered so that the QoS of the CUE can be guaranteed for every realization of the CSI error in the ellipsoid region. The EE objective function of the optimization problem is non-convex and non-linear, and thus this problem cannot be solved by the traditional optimization methods. To solve this problem, first we transform it to an EE maximization problem without uncertain parameters by exploiting the Markov and Cauchy-Schwartz inequality. Then using the fractional programming theory and difference of convex functions optimization method, the robust EE maximization algorithms based on the hard and soft protection method are developed to maximize the system's EE performance, respectively. However, these two algorithms are designed at the cost of the reduced EE of the DUE. Therefore, in order to further improve the EE performance and make a trade-off between the EE performance and the robustness, the iterative update algorithms for the total power constraint and average interference constraint are developed to maximize the system's EE performance, respectively. Simulation results demonstrate the effectiveness of the four proposed EE algorithms and illustrate the trade-off between the EE performance and robustness for the iterative update algorithms.

Improving Physical-Layer Security for Full-duplex Radio aided Two-Way Relay Networks

The power allocation optimization problem is investigated for improving the physical-layer security in two-way relaying networks, where a full-duplex relay based half-jamming protocol (HJP-FDR) is considered. Specially, by introducing a power splitter factor, HJP-FDR divides the relay’s power into two parts: one for forwarding the sources'' signals, the other for jamming. An optimization problem for power split factor is first developed, which is proved to be concave and closed-form solution is achieved. Moreover, we formulate a power allocation problem to determine the sources'' power subject to the total power constraint. Applying the achieved closed-form solutions to the above-mentioned problems, a two-stage strategy is proposed to implement the overall power allocation. Simulation results highlight the effectiveness of our proposed algorithm and indicate the necessity of optimal power allocation.

Impact of clipping noise on the sum rate of NOMA with PD-DCO-OFDM and conventional DCO-OFDM

sIn visible light communication (VLC) systems, a non-orthogonal multiple access (NOMA) scheme is deemed promising technology to offer better spectral efficiency than the Orthogonal multiple access (OMA) scheme. The feasibility of power domain NOMA for VLC system has been studied with different variants of unipolar OFDM schemes. However, few research works have been presented on the impact of clipping noise on the achievable sum rate of NOMA with DC-biased optical OFDM (DCO-OFDM) and polarity divided DCO-OFDM (PD-DCO-OFDM). This paper presents the impact of clipping noise on the achievable sum rate of NOMA-DCO-OFDM and NOMA-PD-DCO-OFDM VLC systems. Moreover, NOMA-DCO-OFDM and NOMA-PD-DCO-OFDM systems are compared based on achievable sum rates for different total power constraints and signal clipping levels. For the two-user scenario, Simulation results have confirmed that NOMA-PD-DCO-OFDM can offer a better sum rate compared to NOMA-DCO-OFDM system.

Chance-Constrained Optimization of Energy Storage Capacity for Microgrids

The optimal storage capacity is a crucial parameter for stable and reliable operation of microgrids in an islanded mode. In this context, an analytical method is developed to robustly formulate and analyze energy storage capacity deploying chance constrained stochastic optimization. More specifically, the goal is to determine an appropriate size for an energy storage to reach a specific loss of load probability (LOLP) in a microgrid with large penetration of renewables considering generation and load forecast error. The total cost is minimized over optimal storage capacity as well as over generators power, while accounting for generation and storage power and energy constraints. It is postulated that the shortage/surplus power will be derived from/injected to the storage system. However, due to stochastic nature of load and renewables and an inevitable forecast error, the renewable generation output or the load power may not be accurately acquired. Thus, the total storage power and energy constraints are posed as chance constraints, for which conservative convex approximations are employed for tractability. In particular, to overcome the difficulty brought about by the large size of the optimization problem, a separable (distributed) structure is pursued, and the dual decomposition method is adopted to obtain optimal solutions. Numerical tests verify the effect of prior knowledge in modeling the uncertainty in optimal choice of storage capacity.

Power allocation and subchannel pairing for BER minimization in MIMO-OFDM AF relay systems

The present study investigates the problem of bit error rate minimization in multi-input-multi-output orthogonal frequency-division multiplexing amplify-and-forward relay systems. It is supposed that channels are frequency selective fading and under a total power constraint. In the multi-antenna transmitter, an independent symbol sequence is transmitted from each antenna. Zero forcing beamforming is performed in the reception and transmission of the relay to cancel out the inter-antenna interference. A power allocation and subchannel pairing scheme is considered as the optimization method. The goal of the optimization problem is to achieve the best bit error rate performance by applying a joint power allocation and subchannel pairing approach for all antennas. To deal with subchannel pairing, at first, we formulate it as a linear assignment problem and then Jonker-Volgenant algorithm is used to solve this problem. The joint scheme is compared with separate power allocation and subchannel pairing for each antenna as the main target. It is found that the joint scheme is superior to the separate method. Simulation results show that the proposed inter-antenna power allocation and subchannel pairing scheme can improve bit error rate and mean square error dramatically compared with separate subchannel pairing and power allocation at the cost of a little increase in complexity.