Power Minimization Problem Research Articles

Broadband photonic frequency measurement based on the frequency-to-carrier phase-shifted mapping and finite extinction ratio

A novel frequency measurement is proposed based on frequency-to-carrier phase-shifted mapping and finite extinction ratio. Due to the frequency dependence of the dispersion phase shift, carrier phase-shifted double-sideband modulation and dispersive effect are combined for effective mapping. Additionally, the finite extinction ratio is introduced to mitigate the influence of unideal parameters on measurement error. To achieve this, a dual-parallel Mach-Zehnder modulator and a dispersion compensating fibre are combined, and a power minimization problem is formulated to establish a mapping table. Theoretical analysis and simulation results show the frequency measurement range over 30 GHz with errors below 180 MHz. Furthermore, the measurement error is reduced below 40 MHz after considering the finite extinction ratio.

Transmit Power Optimization in Multihop Amplify-and-Forward Relay Systems with Simultaneous Wireless Information and Power Transfer

In this paper, we study a multi-hop amplify-and-forward (AF) simultaneous wireless information and power transmission (SWIPT) relay system. Each relay node harvests power using a power split (PS) method from a portion of the received signal, amplifies the remaining received signal, and passes it to the next relay. Based on this system model and signal flow, we derived and solved the convex power minimization problem with the optimal PS ratio. In this case, it was found that using the optimal PS ratio consumed a lower amount of power than when using a fixed PS ratio (0.5). We then investigated the impact of processing cost on the AF-SWIPT system using decoding and forwarding SWIPT as benchmarks, and found that AF-SWIPT was superior.

Secure Unmanned Aerial Vehicle Communication in Dual-Function Radar Communication System by Exploiting Constructive Interference

In contrast from traditional unmanned aerial vehicle communication via unlicensed spectrum, connecting unmanned aerial vehicles with cellular networks can extend their communication coverage and improve the quality of their service. In addition, the emerging dual-functional radar communication paradigm in cellular systems can better meet the requirements of location-sensitive tasks such as reconnaissance and cargo delivery. Based on the above considerations, in this paper, we study the simultaneous communication and target sensing issue in cellular-connected unmanned aerial vehicle systems. Specifically, we consider a two-cell coordinated system with two base stations, cellular unmanned aerial vehicles, and potential aerial targets. In such systems, the communication security issue of cellular unmanned aerial vehicles regarding eavesdropping on their target is inevitable since the main beam of the transmit waveform needs to point to the direction of the target for achieving a sufficient detection performance. Aiming at protecting the privacy of cellular transmission as well as performing target sensing, we exploit the physical layer security technique with the aid of constructive interference-based precoding. A transmit power minimization problem is formulated with constraints on secure and reliable cellular transmission and a sufficient radar signal-to-interference-plus-noise ratio. By specially designing the transmit beamforming vectors at the base stations, the received signals at the cellular users are located in the decision regions of the transmitted symbols while the targets can only receive wrong symbols. We also compare the performance of the proposed scheme with that of the traditional one without constructive interference. The simulation results show that the proposed constructive interference-based strategy can meet the requirements of simultaneous target sensing and secure communication, and also save transmit power compared with the traditional scheme.

Transmission scheme for collaborative‐RIS‐aided NOMA system with multiple channels

AbstractThis paper investigates the combination of collaborative reconfigurable intelligent surface (RIS) with non‐orthogonal multiple access (NOMA) to enhance the quality of service (QoS) in communication systems. By introducing collaborative RIS, a virtual line‐of‐sight (LoS) link can be established between the base station (BS) and the users. In this article, the aim is to minimize the total transmit power under the constraint of each user's QoS by optimizing the phase shifts and the power allocation coefficients. To proceed, two approaches are proposed with different complexities to solve the formulated power minimization problem. Specifically, in the first method, a sub‐channel allocation scheme based on the user locations is developed, and the phase shifts are optimized to obtain the minimum transmit power for fixed channel assignment, which is further addressed by using the alternating optimization and the sequence rotation methods. In the second approach, a joint optimization algorithm that achieves the channel assignment vectors and the phase shift coefficients in an alternative manner, and a sub‐channel assignment algorithm based on the equivalent channel gain is developed. The simulation results show that the proposed transmission scheme has the capability of improving system performance significantly compared with the conventional schemes.

Dynamic Framing and Power Allocation for Real-Time Wireless Networks with Variable-Length Coding: A Tandem Queue Approach

Ensuring high reliability and low latency poses challenges for numerous applications that require rigid performance guarantees, such as industrial automation and autonomous vehicles. Our research primarily concentrates on addressing the real-time requirements of ultra-reliable low-latency communication (URLLC). Specifically, we tackle the challenge of hard delay constraints in real-time transmission systems, overcoming this obstacle through a finite blocklength coding scheme. In the physical layer, we encode randomly arriving packets using a variable-length coding scheme and transmit the encoded symbols by truncated channel inversion over parallel channels. In the network layer, we model the encoding and transmission processes as tandem queues. These queues backlog the data bits waiting to be encoded and the encoded symbols to be transmitted, respectively. This way, we represent the system as a two-dimensional Markov chain. By focusing on instances when the symbol queue is empty, we simplify the Markov chain into a one-dimensional Markov chain, with the packet queue being the system state. This approach allows us to analytically express power consumption and formulate a power minimization problem under hard delay constraints. Finally, we propose a heuristic algorithm to solve the problem and provide an extensive evaluation of the trade-offs between the hard delay constraint and power consumption.

Robust beamforming design for passive RIS‐assisted NOMA systems

AbstractA transmission power minimization problem for a reconfigurable intelligent surface (RIS) aided non‐orthogonal multiple access (NOMA) network has been studied here, which has assumed the channel state information is imperfect. The channel error in this paper has been modeled as two different error models, that is, bounded error model and statistical error model. First, a two‐step algorithm is proposed to decouple the decoding order and optimization variables under bounded error model. Then, for the statistical error model, the alternating optimization method is adopted to decouple optimization variables. Finally, the performance difference is compared between the proposed beamforming scheme and the non‐RIS scheme from two key parameters, the number of reflected elements and the error factor. Simulation results verify that passive RIS has the advantage on the system performance compared with the scheme without RIS.

Asynchronous Bidirectional Communication in Cell-Free Networks

We consider a bidirectional communication between two single-antenna transceivers using multiple multi-antenna access points (APs) in a cell-free network architecture. In such a network, because of different propagation delays associated with different APs, the end-to-end link is a multi-path channel that results in inter-symbol-interference (ISI) in the signals received at the transceivers. To tackle ISI, we resort to cyclic prefix (CP) assisted block transmission of the information symbols and employ joint pre- and post-channel equalizers at both the transceivers to mitigate the impact of intra-block interference. Considering the amplify-and-forward technique at the APs, we cast the joint design of equalizers, beamforming matrices, and transceivers’ transmit powers as a power minimization problem while guaranteeing predefined data rates at the transceivers. Assuming symmetric beamforming matrices at the APs, we devise a semi-closed-form solution for this problem. We prove rigorously that at the optimum only a synchronous subset of the APs should participate in the information exchange between the two transceivers. This is achieved by proving that at the optimum, the pre-equalizer matrices should be unitary and the post-equalizer matrices should be invertible.

QoS-Guaranteed Hybrid Beamforming Design for Multi-User Systems With Finite-Resolution Phase Shifters

Massive multiple input multiple output (MIMO) technology is a key enabler of the next generation wireless communications. The partially-connected hybrid beamforming architecture is attractive in massive MIMO systems for its reduced cost, power consumption, and hardware complexity. On the other hand, the specific analog beamforming structure and finite-resolution in phase shifters complicate the beamforming design. In this paper, we study the hybrid beamforming design for the partially-connected architecture, where users can have multiple antennas and different requirements on quality of service (QoS). A transmit power minimization problem is formulated. The beamforming design needs to be aligned to discrete phase values due to the practical limitations. Such problem is non-convex and is hard to solve. We propose an effective algorithm for this problem. In particular, the penalty-based method is used to decouple the variables. The original problem is decomposed into several sub-problems. The block prox-linear method is applied to solve the sub-problems alternatively with convergence guarantee. We show the effectiveness and robustness of our proposed algorithm via simulations. Our proposed algorithm with low resolution phase shifters achieves better performance with lower transmit power than existing methods.

Energy Efficiency Optimization for Backscatter Enhanced NOMA Cooperative V2X Communications Under Imperfect CSI

Automotive-Industry 5.0 will use beyond fifth-generation (B5G) technologies to provide robust, computationally intelligent, and energy-efficient data sharing among various onboard sensors, vehicles, and other devices. Recently, ambient backscatter communications (AmBC) have gained significant interest in the research community for providing battery-free communications. AmBC can modulate useful data and reflect it towards near devices using the energy and frequency of existing RF signals. However, obtaining channel state information (CSI) for AmBC systems would be very challenging due to no pilot sequences and limited power. As one of the latest members of multiple access technology, non-orthogonal multiple access (NOMA) has emerged as a promising solution for connecting large-scale devices over the same spectral resources in B5G wireless networks. Under imperfect CSI, this paper provides a new optimization framework for energy-efficient transmission in AmBC enhanced NOMA cooperative vehicle-to-everything (V2X) networks. We simultaneously minimize the total transmit power of the V2X network by optimizing the power allocation at BS and reflection coefficient at backscatter sensors while guaranteeing the individual quality of services. The problem of total power minimization is formulated as non-convex optimization and coupled on multiple variables, making it complex and challenging. Therefore, we first decouple the original problem into two sub-problems and convert the nonlinear rate constraints into linear constraints. Then, we adopt the iterative sub-gradient method to obtain an efficient solution. For comparison, we also present a conventional NOMA cooperative V2X network without AmBC. Simulation results show the benefits of our proposed AmBC enhanced NOMA cooperative V2X network in terms of total achievable energy efficiency.

Optimization for Reflection and Transmission Dual-Functional Active RIS-Assisted Systems

Reconfigurable intelligent surface (RIS) has been deemed as one of potential components of future wireless communication systems because it can adaptively manipulate the wireless propagation environment with low-cost passive devices. However, due to the severe double path loss, the traditional passive RIS can provide sufficient gain only when receivers are very close to the RIS. Moreover, RIS cannot provide signal coverage for the receivers at the back side of it. To address these drawbacks in practical implementation, we introduce a novel reflection and transmission dual-functional active RIS (DF-ARIS) architecture in this paper, which can simultaneously realize reflection and transmission functionalities with active signal amplification to significantly extend signal coverage and enhance the quality-of-service (QoS) of all users. The problem of joint transmit beamforming and dual-functional active RIS design is investigated in RIS-enhanced multiuser multiple-input single-output (MU-MISO) systems. Both sum-rate maximization and power minimization problems are considered. To address their non-convexity, we develop efficient iterative algorithms to decompose them into several separate design problems, which are efficiently solved by exploiting fractional programming (FP) and Riemannian-manifold optimization techniques. Simulation results demonstrate the superiority of the proposed dual-functional active RIS architecture and the effectiveness of our proposed algorithms over various benchmark schemes.

Energy-Efficient Beamforming Design for RIS-Aided MIMO Downlink Communication With SWIPT

This paper investigates an energy/power-efficient simultaneous wireless information and power transfer (SWIPT)-enabled reconfigurable intelligent surface (RIS)-assisted multi-input multi-output (MIMO) communication network, where a base station (BS) communicates with multiple information receivers (IRs) and energy receivers (ERs) simultaneously with the aid of a RIS. We formulate a power minimization problem and jointly optimize the active beamforming matrix at the BS and passive beamforming matrix at the RIS subject to the constraint of the minimum required rate at each IR while ensuring the minimum energy harvesting requirement of ERs. Due to the non-convex nature of the formulated problem, we transform the minimum rate constraint into a simpler form by adopting a mean square error (MSE) based approach. Next, an alternating optimization (AO) method is adopted to transform the main non-convex problem into two simpler sub-problems, for obtaining the optimal active and passive beamforming matrices, respectively. Thereafter, computationally efficient algorithms are proposed to determine the optimal solutions of each sub-problem utilizing optimization tools such as Lagrangian dual decomposition, sub-gradient method, majorization-minimization (MM) and pricing-based approaches. Then, we also propose an AO-based iterative algorithm that obtains the optimal values of both matrices iteratively by repeatedly using the aforementioned sub-optimal solutions. We also discuss the impact of imperfect channel state information (CSI) on the performance of the considered network and demonstrate the effectiveness of the proposed algorithm in providing an efficient beamforming design for the same. In addition to this, we highlight the impact of key system parameters such as the number of reflecting elements, and the minimum rate constraint. Finally, we establish that the use of an RIS in such a network along with the proposed algorithm provides a power saving of approximately 10%-26% compared to the other traditional schemes to achieve the same quality of service.

Robust Energy-Efficient Transmission for Cell-Free Massive MIMO Systems with Imperfect CSI

In this paper, we investigate a long-term power minimization problem of cell-free massive multiple-input multiple-output (MIMO) systems. To address this issue and to ensure the system queue stability, we formulate a dynamic optimization problem aiming to minimize the average total power cost in a time-varying system under imperfect channel conditions. The problem is then converted into a real-time weighted sum rate maximization problem for each time slot using the Lyapunov optimization technique. We employ approximation techniques to design robust sparse beamforming, which enables energy savings of the network and mitigates channel uncertainty. By applying direct fractional programming (DFP) and alternating optimization, we can obtain a locally optimal solution. Our DFP-based algorithm minimizes the average total power consumption of the network while satisfying the quality of service requirements for each user. Simulation results demonstrate the rapid convergence of the proposed algorithm and illustrate the tradeoff between average network power consumption and queue latency.

User grouping and resource management in efficient NOMA‐OMA transmission scheme for infotainment message dissemination in VANETs

AbstractThe data distribution for infotainment services at vehicular ad‐hoc networks (VANETs) has become a research hotspot in recent years. Non‐orthogonal multiple access (NOMA) is accepted as an enabling technology for 5G and beyond due to its improved spectral efficiency. In this work, we consider a VANET communication scenario where users have common data demands such as high‐density maps, local entertainment/shopping options or other popular media content. For such a scenario, we propose an efficient clustering scheme together with a hybrid NOMA‐OMA scheme for improved spectral and power efficiency. For this setup, we also develop an optimal bandwidth allocation strategy to improve the power efficiency further. We formulate a one dimensional nonlinear power minimization problem such that the bandwidth allocation for the system can be optimized. The complexity and optimality analysis of optimization algorithms used for power minimization are performed. The improved performance of the proposed scheme in terms of power efficiency, spectral efficiency and latency performance is showcased in comparison to conventional NOMA and OMA approaches.

RIS-Level SIC for Uplink Cascaded-RIS Assisted NOMA System

A brand-new framework for cascaded-reconfigurable intelligent surface (RIS) empowered multi-antenna non-orthogonal multiple access (NOMA) system is conceived, wherein RISs are deployed to serve their associated users and assist data transmission for the farther RISs as well. A new concept of RIS-level successive interference cancellation (RSIC) is developed to eliminate the inter-RIS interference. With the devised framework, a transmit power minimization problem is formulated by collaboratively designing each user’s transmit power, the RISs’ phase shifts, and the BS’s equalizers. Specifically, a parallel iteration method is developed to solve the subproblem of jointly optimizing transmit power and equalizers, whereas a sequential phase-rotation algorithm is proposed to address the subproblem of phase shift optimization. It is showed by simulations that the proposed scheme outperforms the existing benchmark schemes in terms of total transmit power.

Intelligent Reconfigurable Surface enhanced Ambient Backscatter Communication enabled Wireless Body Area Network

This paper considers an Intelligent Reconfigurable Surface (IRS)-enhanced Ambient Backscatter Communication (AmBC)-enabled Wireless Body Area Network (WBAN) system. We study the Base Station (BS) transmit power minimization problem, where the BS’s transmit beamforming vector and IRS’s reflecting coefficients are jointly optimized, subjected to the Signal-to-Noise Ratio (SNR) requirements of intra-WABN communication and throughput requirement of primary communication. To solve the non-convex problem, a near-optimal algorithm based on Semi-Definite Relaxation (SDR) and Successive Convex Approximation (SCA), and a low complexity algorithm based on IRS elements partition are proposed. Numerical results show that the two proposed algorithms considerably outperform the baseline schemes.

Energy Efficient Wireless Crowd Labeling: Joint Annotator Clustering and Power Control

The unprecedented growth of mobile data traffic has fueled the deployment of artificial intelligence (AI) at the network edge, while distilling the intelligence from raw data by machine learning requires tremendous labelling effort. To overcome this challenge, wireless crowd labelling (WCL) is proposed for efficient data labelling by exploiting billions of available mobile annotators and the multicasting property of wireless channels. A WCL system is considered in this paper where unlabelled data (objects) are multicast via fading channels to different clusters of annotators for repetition labelling to improve the accuracy. Given the desired labelling accuracy, the superposition coding technique together with the repetition labelling scheme give rise to a new tradeoff between radio-and-annotator resource consumption. Building on such tradeoff, the annotator clustering and transmit power control are jointly optimized to maximize the labelling throughput (i.e., the number of labelled objects) or minimize the power consumption, resulting in NP-hard integer programming problems. To solve these problems, the optimal structure of annotator clustering is derived by exploiting the property that the power allocation for multicasting objects tends to compensate for the worst channel among the annotators in each cluster. Based on such structure, the throughput maximization problem can be recognized as a longest-path problem and solved by means of branch-and-bound, while the power minimization problem can be recasted to a shortest-path problem and solved by means of forward dynamic programming. The solution approaches can be further simplified when the channels are symmetric by merging the same nodes and cutting the identical paths in the path graph. In addition, exact polices are derived for the special cases where either the annotators or power are constrained. Last, simulation results are presented to demonstrate the performance of our proposed joint designs.

Cellular Network Enabled Energy-Harvesting Secure Communications for Full-Duplex D2D Links

This article investigates the secure transmissions for a wireless powered full-duplex (FD) device-to-device (D2D) overlay system. To coordinate the cellular downlink transmissions and the D2D transmissions, we propose a two-phase transmission protocol, where the first phase is dedicated to the transmissions of information and energy from the base station (BS) to its users and the devices, respectively, and the second phase is dedicated to information exchanging between the two devices over an FD link overheard by either active or passive eavesdroppers. In the case of active eavesdroppers, perfect channel state information (CSI) is assumed to be available, whereas for passive eavesdroppers, only statistic CSI is available. Both self-interference (SI) mitigation and BS-aided cooperative jamming are considered for the D2D secure transmissions. For system design, nonconvex power minimization problems under transmission rate constraints are formulated and convex approximated for efficiently obtaining numerical solutions. Simulation results show that the proposed scheme can well coordinate the cellular transmissions and the FD-D2D secure transmissions, while the cooperative jamming strategy can enhance the D2D transmission security, especially in the case of passive eavesdroppers.

Joint Beamforming Design for Intelligent Omni Surface Assisted Wireless Communication Systems

Intelligent reflecting surface (IRS) has been widely considered as one of the key enabling techniques for future wireless communication networks owing to its ability of dynamically controlling the phase shift of reflected electromagnetic (EM) waves to construct a favorable propagation environment. While IRS only focuses on signal reflection, the recently emerged innovative concept of intelligent omni-surface (IOS) can provide the dual functionality of manipulating reflecting and transmitting signals. Thus, IOS is a new paradigm for achieving ubiquitous wireless communications. In this paper, we consider an IOS-assisted multi-user multi-input single-output (MU-MISO) system where the IOS utilizes its reflective and transmissive properties to enhance the MU-MISO transmission. Both power minimization and sum-rate maximization problems are solved by exploiting the second-order cone programming (SOCP), Riemannian manifold, weighted minimum mean square error (WMMSE), and block coordinate descent (BCD) methods. Simulation results verify the advancements of the IOS for wireless systems and illustrate the significant performance improvement of our proposed joint transmit beamforming, reflecting and transmitting phase-shift, and IOS energy division design algorithms. Compared with conventional IRS, IOS can significantly extend the communication coverage, enhance the strength of received signals, and improve the quality of communication links.

Robust Beamforming Design With Finite Blocklength for URLLC

Ultra-reliable and low-latency communications (URLLC) are essential for mission-critical applications, such as telemedicine, automatic drive, etc. In the design of URLLC, the robustness of multi-user beamforming transmission scheme is critical and challenging. To this end, we consider a robust beamforming design in the finite blocklength regime for a multi-user multi-antenna downlink system in the case of imperfect channel state information at the transmitter. A transmission power minimization problem is formulated to optimize the beamforming vectors under the premise of guaranteeing the requirements on transmission latency, reliability and the target user rates, which is non-convex. To solve it, we first reformulate the problem into a tractable form by using the convexity and concavity of asymptotic capacity in the finite blocklength regime, then adopt S-Procedure to convert the infinite constraints into finite ones. Finally, the Gaussian randomization method and the penalty function method are utilized to generate a feasible solution to the original optimization problem and to provide a good rank-one approximation, respectively. The simulation results confirm the robustness and effectiveness of the beamforming design.

Power Minimization in Multi-Antenna Transmitter Aided Bidirectional Tag-to-Device Communications for IoT

Bidirectional device-to-device (D2D) communications with energy-constrained devices hold the potential to revolutionize the low-power communication landscape and provide a means to realize the aim of Internet-of-Things (IoT). In this paper, we aim to explore a communication environment where a multi-antenna transmitter facilitates communication between two users equipped with two different technologies — backscattering and radio frequency based energy harvesting. Under such a setting, we aim to minimize the transmit power over a set of constraints by considering the traditional linear and the more practical nonlinear (sigmoid) energy harvesting model. Henceforth, we propose a novel optimal solution approach, exploiting the geometric interpretation of constraints and interdependency of optimization variables and the performance metric, to solve the formulated non-convex problem for the multi-antenna transmitter case for both the energy harvesting models considered. In addition, we revisit the power minimization problem for the single-antenna transmitter case, solved in our previous work, to demonstrate the applicability of the current solution approach. Furthermore, to establish a fair balance between the performance and the computation-intensive nature of the proposed optimal solution, we present two low complexity sub-optimal solution approaches leveraging the analysis carried out for the single antenna transmitter case. Finally, using the numerical simulations, we assess the performance of our system and present a comparison between the proposed solution approaches by varying some key parameters of our simulation setting.