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Equitable 6G Access Service Via Cloud-Enabled HAPS for Optimizing Hybrid Air-Ground Networks

IEEE TRANSACTIONS ON COMMUNICATIONS 2024年第5期72卷 2959-2973页

作者： Alghamdi, Rawan Dahrouj, Hayssam Al-Naffouri, Tareq Y. Alouini, Mohamed-Slim Div Comp Elect & Math Sci & Engn CEMSE Elect & Comp Engn Program Thuwal 239556900 Saudi Arabia Univ Sharjah Dept Elect Engn Sharjah U Arab Emirates

The evolvement of wireless communication services concurs with significant growth in data traffic, thereby inflicting stringent requirements on terrestrial networks. This work invigorates a connectivity solution that integrates aerial and terrestrial communications with a cloud-enabled high-altitude platform station (C-HAPS) to promote an equitable connectivity landscape. The C-HAPS system is connected to terrestrial base-stations and hot-air balloons via a data-sharing fronthauling strategy. The base-stations and hot-air balloons are then grouped into disjoint clusters and coordinately serve both aerial and terrestrial users. The paper focuses on determining the user-to-transmitter scheduling policy and the associated users' beamforming vectors in the downlink direction of the considered network by maximizing two different objectives: the sum-rate and sum-of-log of the long-term average rate, both subject to limited transmit power and finite fronthaul capacity. The paper uses well-chosen convexification and approximation steps, such as fractional programming and sparse beamforming via re-weighted & ell;(0) -norm approximation, to solve the two non-convex discrete and continuous optimization problems using numerical iterative optimization algorithms. The results outline the gain illustrated through equitable access service in crowded and unserved areas and showcase the numerical benefits stemming from the proposed C-HAPS coordination of hot-air balloons and terrestrial base-stations for empowering the digital inclusion framework.

关键词： Array signal processing Resource management Interference Cloud computing Backhaul networks Wireless communication programming High-altitude platforms cloud networks fractional programming proportional fairness

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Convexification techniques for fractional programs

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MATHEMATICAL programming 2024年 1-43页

作者： He, Taotao Liu, Siyue Tawarmalani, Mohit Shanghai Jiao Tong Univ Antai Coll Econ & Management Shanghai Peoples R China Carnegie Mellon Univ Tepper Sch Business Pittsburgh PA 15213 USA Purdue Univ Mitchell E Daniels Jr Sch Business W Lafayette IN USA

This paper develops a correspondence relating convex hulls of fractional functions with those of polynomial functions over the same domain. Using this result, we develop a number of new reformulations and relaxations for fractional programming problems. First, we relate 0-1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0\mathord {-}1$$\end{document} problems involving a ratio of affine functions with the boolean quadric polytope, and use inequalities for the latter to develop tighter formulations for the former. Second, we derive a new formulation to optimize a ratio of quadratic functions over a polytope using copositive programming. Third, we show that univariate fractional functions can be convexified using moment hulls. Fourth, we develop a new hierarchy of relaxations that converges finitely to the simultaneous convex hull of a collection of ratios of affine functions of 0-1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0\mathord {-}1$$\end{document} variables. Finally, we demonstrate theoretically and computationally that our techniques close a significant gap relative to state-of-the-art relaxations, require much less computational effort, and can solve larger problem instances.

关键词： fractional programming Boolean quadric polytopes Quadratic optimization Copositive optimization Moment hull Assortment optimization Distillation

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Energy-Efficiency Optimization With Model Convexification for Wireless Ad Hoc Networks With Multi-Packet Reception Capability

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2024年第4期23卷 2864-2881页

作者： Zhou, Jianshan Tian, Daxin Qu, Guixian Sheng, Zhengguo Duan, Xuting Leung, Victor C. M. Beihang Univ Sch Transportat Sci & Engn Beijing Key Lab Cooperat Vehicle Infrastruct Syst Beijing Peoples R China Beihang Univ Res Inst Aeroengine Aeroengine Syst Collaborat Design Ctr Beijing 100191 Peoples R China Univ Sussex Dept Engn & Design Richmond 3A09 England Univ British Columbia Dept Elect & Comp Engn Vancouver BC V6T 1Z4 Canada

Energy efficiency is a significant requirement of resource management and design optimization in information networks. In this article, we propose an iterative fractional programming framework embedded with a distributed primal-dual extra-gradient projection algorithm, which addresses a wide class of the energy-efficiency optimization problems in wireless ad hoc networks with full-duplex radios and multi-packet reception capability. Specifically, we propose a model convexification mechanism by joining an affine transformation and an exponential transformation into the nonlinear fractional programming, which enables us to deal with the challenge arising from the complexity and non-convex structure of the original problem. With the model convexification, we can map the non-convex power control space into a convex space and equivalently derive a sequence of convex subproblems, which relaxes the convexity assumption widely adopted in the existing literature. We further propose a distributed primal-dual algorithm based on extra-gradient projection to solve the convex subproblem at each iteration of the fractional programming. The convergence of the proposed iterative fractional programming and the distributed optimization method is theoretically proven. Numerical results also verify the proposed method and demonstrate its superior performance over other representative distributed and centralized schemes in terms of achieving global energy efficiency.

关键词： programming Optimization Mobile ad hoc networks Mathematical models Full-duplex system Linear programming Couplings Convex optimization distributed computation energy efficiency fractional programming wireless ad hoc networks

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Cooperative Beamforming for Double-RIS Assisted CoMP Systems

IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING

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IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING 2024年第4期8卷 1917-1929页

作者： Chen, Jian Sun, Yuchen Jia, Jie Yin, Baoxin Wang, Xingwei Northeastern Univ Engn Res Ctr Secur Technol Complex Network Syst Sch Comp Sci & Engn Minist Educ Shenyang 110819 Peoples R China Northeastern Univ Key Lab Intelligent Comp Med Image Minist Educ Shenyang 110819 Peoples R China

Energy efficiency (EE) has become a key performance indicator in designing future wireless networks. In this regard, we propose a novel two reconfigurable intelligent surfaces (RISs) assisted coordinated multipoint (CoMP) network, where two RISs cooperate to reduce energy consumption by constructing an intelligent radio environment. Aiming to maximize this system's energy efficiency (EE), the joint optimization problem on the cooperative beamforming among base stations (BSs) and passive beamforming among RISs, subject to each user's data rate requirement, is formulated. An alternative optimization algorithm is proposed by decoupling it into a cooperative beamforming subproblem among BSs and a cooperative reflective coefficients design subproblem among RISs. Dinkelbach's transform and complex fractional programming algorithms are also invoked to transform these two subproblems into convex optimization problems and obtain the optimal solution for each sub-problem. Numerical results validate the proposed algorithm's feasibility, fast convergence, and flexibility. It also shows that the proposed scheme with cooperative beamforming design for both BSs and RISs outperforms that without RIS and that with randomly initialized RISs.

关键词： cooperative beamforming CoMP fractional programming fractional programming RIS RIS RIS energy efficiency energy efficiency energy efficiency energy efficiency energy efficiency fractional programming RIS

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Successive upper approximation methods for generalized fractional programs

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RAIRO-OPERATIONS RESEARCH 2024年第4期58卷 3119-3142页

作者： Boufi, Karima Fadil, Abdessamad Roubi, Ahmed Hassan First Univ Settat Inst Super Sci Sante Settat Morocco Lab MISI Settat Morocco Hassan First Univ Settat Fac Sci & Tech Lab MISI Settat Morocco

The majorization approximation procedure consists in replacing the resolution of a non-linear optimization problem by solving a sequence of simpler ones, whose objective and constraint functions upper estimate those of the original problem. For generalized fractional programming, i.e., constrained minimization programs whose objective functions are maximums of finite ratios of functions, we propose an adapted scheme that simultaneously upper approximates parametric functions formed by the objective and constraint functions. For directionally convex functions, that is, functions whose directional derivatives are convex with respect to directions, we will establish that every cluster point of the generated sequence satisfies Karush-Kuhn-Tucker type conditions expressed in terms of directional derivatives. The proposed procedure unifies several existing methods and gives rise to new ones. Numerical problems are solved to test the efficiency of our methods, and comparisons with different approaches are given.

关键词： fractional programming optimality conditions successive majorizations methods successive quadratic approximation gradient method

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An Iterative Fuzzy Goal programming Method to Solve Fuzzified Multiobjective fractional programming Problems

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48th Annual Convention of Computer Society of India (CSI)

作者： Kumar, Mousumi Sen, Shyamal Pal, Bijay Baran Univ Kalyani Dept Math Kalyani 741235 W Bengal India Alipurduar Coll Dept Math Alipurduar Court 736122 W Bengal India BKC Coll Dept Math Kolkata 700108 India

ISBN: (纸本)9783319031071

This paper presents a fuzzy goal programming (FGP) approach for modeling and solving multiobjective fractional programming problems (MOFPPs) with fuzzy numbers parameter sets. In the proposed approach, first the notion of a-cut in fuzzy sets (FSs) is used to transform a problem into conventional MOFPP by using the tolerance membership functions in FSs. In model formulation, membership functions are converted into fuzzy goals for measuring the degree of satisfaction of decision maker (DM) with the solution for achievement of fuzzily described objectives of the problem. In the solution process, an iterative parametric method is addressed within the framework of minsum FGP model to reach the highest membership value (unity) to the extent possible in the decision making environment. The efficiency of the proposed approach is illustrated by a numerical example. The model solution is also compared with the solution obtained by using other approaches studied previously.

关键词： fractional programming Fuzzy Goal programming Iterative parametric method Membership functions Triangular fuzzy number

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Joint Active and Passive Beamforming Design for Hybrid RIS-Aided Integrated Sensing and Communication

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China Communications 2024年第10期21卷 101-112页

作者： Chu Hongyun Yang Mengyao Pan Xue Xiao Ge School of Communications and Information Engineering Xi'an University of Posts and TelecommunicationsXi'an 710121China

Integrated sensing and communication(ISAC) is considered an effective technique to solve spectrum congestion in the future. In this paper, we consider a hybrid reconfigurable intelligent surface(RIS)-assisted downlink ISAC system that simultaneously serves multiple single-antenna communication users and senses multiple targets. Hybrid RIS differs from fully passive RIS in that it is composed of both active and passive elements, with the active elements having the effect of amplifying the signal in addition to phase-shifting. We maximize the achievable sum rate of communication users by collaboratively improving the beamforming matrix at the dual function base station(DFBS) and the phase-shifting matrix of the hybrid RIS, subject to the transmit power constraint at the DFBS, the signal-to-interference-plus-noise-ratio(SINR) constraint of the radar echo signal and the RIS constraint are satisfied at the same time. The builtin RIS-assisted ISAC design problem model is significantly non-convex due to the fractional objective function of this optimization problem and the coupling of the optimization variables in the objective function and constraints. As a result, we provide an effective alternating optimization approach based on fractional programming(FP) with block coordinate descent(BCD)to solve the optimization variables. Results from simulations show that the hybrid RIS-assisted ISAC system outperforms the other benchmark solutions.

关键词： alternating optimization fractional programming hybrid reconfigurable intelligent surface integrated sensing and communication joint active and passive beamforming

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Sum-Rate Maximization for RIS-IoV: From Instantaneous to Statistical CSI

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2024年第7期23卷 8071-8084页

作者： Duan, Wei Gu, Xiaohui Zhang, Guoan Wen, Miaowen Ding, Zhiguo Ho, Pin-Han Nantong Univ Sch Informat Sci & Technol Nantong College of E Peoples R China Nantong Univ Sch Informat Sci & Technol Nantong 510640 Peoples R China Nantong Univ Sch Informat Sci & Technol Nantong Peoples R China Nantong Univ Sch Informat Sci & Technol Nantong ON N2L 3G1 Peoples R China

To fully exploit the potential of reconfigurable intelligent surface (RIS), the controllable channel state information (CSI) should be accurate for its future applications. Unfortunately, in vehicular communications, obtaining exact instantaneous CSI presents substantial challenges. Moreover, even with an instantaneous CSI acquisition, a processing latency for RIS phase shift adaption might occur before the vehicular system reacts to the instantaneous CSI information. To effectively introduce RIS into Internet of vehicle (IoV) networks, we employ a more realistic statistical CSI approach in designing RIS-assisted vehicular communication systems that are robust to the general characteristics of the channel, rather than its instantaneous fluctuations. We present a practical system framework, where a roadside unit employs an RIS to facilitate indirect wireless communications for vehicle-to-vehicle (V2V) communications. Particularly, the direct links between vehicles are susceptible to blockages caused by surrounding obstacles/vehicles. The deployment of RIS is to establish supplementary communication links between a multi-antenna vehicle source (VS) and multiple vehicular users (VUs) as they traverse areas with a poor service coverage. With the objective to maximize the time-averaged sum-rate of VUs, instead of instantaneous CSI, we rely on the delayed statistical CSI feedback to design active beamforming at the VS and passive beamforming at RIS. Moreover, we develop an efficient algorithm, named JAPBNB, which leverages the fractional programming technique to find a stationary solution for the formulated sum-of-logarithms-of-ratio problem. Specifically, a non-convex block coordinate descent (BCD) approach, collaborating with the alternating direction method of multipliers (ADMM), is applied for the joint optimization of active and passive beamforming. Finally, the complexity and convergence of the proposed JAPBNB algorithm are thoroughly discussed and validated. Simula

关键词： Wireless communication Array signal processing Vehicle dynamics Heuristic algorithms Optimization Vehicular ad hoc networks Real-time systems Reconfigurable intelligent surface vehicular communications active and passive beamforming fractional programming

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Half-Duplex APs With Dynamic TDD Versus Full-Duplex APs in Cell-Free Systems

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IEEE TRANSACTIONS ON COMMUNICATIONS 2024年第7期72卷 3856-3872页

作者： Chowdhury, Anubhab Murthy, Chandra R. Indian Inst Sci Dept Elect & Commun Engn Bengaluru 560012 India

In this paper, we present a comparative study of half-duplex (HD) access points (APs) with dynamic time-division duplex (DTDD) and full-duplex (FD) APs in cell-free (CF) systems. Although both DTDD and FD CF systems support concurrent downlink (DL) transmission and uplink (UL) reception capability, the sum spectral efficiency (SE) is limited by various cross-link interferences. We first present a novel pilot allocation scheme that minimizes the pilot length required to ensure no pilot contamination among the user equipments (UEs) served by at least one common AP. Then, we derive the sum SE in closed form, considering zero-forcing combining and precoding along with the signal-to-interference plus noise ratio optimal weighting at the central processing unit. We also present a provably convergent algorithm for joint UL-DL power allocation and UL/DL mode scheduling of the APs (for DTDD) to maximize the sum SE. Further, the proposed algorithms are precoder and combiner agnostic and come with closed-form update equations for the UL and DL power control coefficients. Our numerical results illustrate the superiority of the proposed pilot allocation and power control algorithms over several benchmark schemes and show that the sum SE with DTDD can outperform an FD CF system with similar antenna density. Thus, DTDD combined with CF is a promising alternative to FD that attains the same performance using HD APs, while obviating the burden of intra-AP interference cancellation.

关键词： Resource management Power control Signal processing algorithms Scheduling Cost function Channel estimation MIMO communication Cell-free MIMO full-duplex dynamic TDD pilot allocation fractional programming

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Information and sensing beamforming optimization for multi-user multi-target MIMO ISAC systems

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EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING 2023年第1期2023卷 15页

作者： Zhu, Minghe Li, Lei Xia, Shuqiang Chang, Tsung-Hui Chinese Univ Hong Kong Sch Sci & Engn Shenzhen 518100 Shenzhen Peoples R China Shenzhen Res Inst Big Data Shenzhen 518100 Peoples R China ZTE Corp Shenzhen 518057 Peoples R China State Key Lab Mobile Network & Mobile Multimedia T Shenzhen 518055 Peoples R China

Integrated sensing and communication (ISAC) has been envisioned as a key enabler in the next-generation wireless networks. In this paper, we consider the joint information and sensing beamforming design in a multi-user and multi-target multi-input multi-output ISAC system, where a transmit BS and a sensing BS collaborate to sense targets, and the transmit BS sends information streams to communication users at the same time. To optimize the sensing performance and guarantee the communication throughput, we formulate a joint beamforming design problem to minimize the trace of the weighted Cramer-Rao bound of target parameters subject to the sum-rate constraint. The problem is challenging to solve due to the intricate non-convex objective function and constraints. We firstly exploit the weighted mean square error minimization (WMMSE) and semidefinite relaxation (SDR) techniques to devise a WMMSE-SDR algorithm that can achieve a KKT point of the problem. The SDR can be shown to be tight for a subproblem in the WMMSE-SDR algorithm, which implies zero duality for the subproblem. Based on this property and fractional programming techniques, we further reformulate the beamforming problem as a min-max form with simple constraints which then can be efficiently solved by first-order min-max optimization algorithms. Finally, the proposed algorithms are evaluated extensively in simulations. Numerical results show that both proposed algorithms can achieve promising performance in sensing and communication, and the low-complexity algorithm has a significantly reduced computation time.

关键词： MUMT-MIMO ISAC Joint beamforming CRB Sum rate WMMSE Semidefinite relaxation fractional programming

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