Power Allocation for Multiuser Cooperative Communication Networks Under Relay-Selection Degree Bounds

Fang, Haoran; Lin, Xingqin; Lok, Tat-Ming

doi:10.1109/tvt.2012.2200705

Cited by 10 publications

(6 citation statements)

References 26 publications

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“…Furthermore, h nm and ℓ nm typically remain unchanged over a block of transmitted/relaying signals, i.e., block fading. On the other hand, x x x nm = 0 means that relay n is disconnected from both user m and destination m. To control how the N relays are used to help M source-destination pairs, the number of relays assigned to each user shall be limited to at most N R [26], [29]:…”

Section: Joint Beamforming and Relay Selection With Orthogonal Tmentioning

confidence: 99%

“…In particular, joint power allocation and relay assignment problems in orthogonal multi-user scenarios have recently been considered in [25]- [29], either under a game-theoretical framework or by adopting a maximum-ratiocombining receiver. By relaxing the binary constraints {0, 1} of relay assignment to a box constraint on [0, 1], the optimization problems in these papers become convex programs.…”

Section: Introductionmentioning

confidence: 99%

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Joint Optimization of Cooperative Beamforming and Relay Assignment in Multi-User Wireless Relay Networks

Che

Tuan

Nguyen

2014

IEEE Trans. Wireless Commun.

153

125

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This paper considers joint optimization of cooperative beamforming and relay assignment for multi-user multirelay wireless networks to maximize the minimum of the received signal-to-interference-plus-noise ratios (SINR). Separated continuous optimization of beamforming and binary optimization of relay assignment already pose very challenging programs. Certainly, their joint optimization, which involves nonconvex objectives and coupled constraints in continuous and binary variables, is among the most challenging optimization problems. Even the conventional relaxation of binary constraints by continuous box constraints is still computationally intractable because the relaxed program is still highly nonconvex. However, it is shown in this paper that the joint programs fit well in the d.c (difference of two convex functions/sets) optimization framework. Efficient optimization algorithms are then developed for both cases of orthogonal and nonorthogonal transmission by multiple users. Simulation results show that the jointly optimized beamforming and relay assignment not only save transmission bandwidth but can also maintain well the network SINRs. Index Terms-Cooperativebeamforming, power allocation, relay selection, relay assignment, wireless relay networks, d.c. programming. 1536-1276 (c) , IEEE Transactions on Wireless Communications 2 straints. Although these d.c. programs are still very hard, they motivate exploring hidden convex structures of the problem at hand in order to obtain the constructive solutions [36], [37]. It has been recognized for a long time [36] that the d.c. structure of binary constraints has yet to be explored as the binary constraints seem to be more suitable in a d.m. (difference of two monotonic functions/sets) setting [38], [39]. Moreover, different from a binary quadratic problem [40], which has been successfully solved by d.c. optimization, the constructive d.c.representations of the mixed-binary programs considered in the present paper are not available. Through elegant variable changes and effective approximations, our contribution is to reformulate these problems as tractable d.c. programs, which become solvable by d.c. iterations of polynomial complexity and also re-optimization processes. Simulation results show that the proposed computational procedures are capable of locating approximation solutions that are very close to the global optimal solutions. This is evidenced by the fact that the approximation solutions achieve SINR performances that are very close to their upper bounds.The paper is structured as follows. Section II provides a fundamental background on a class of mixed binary optimization and d.c. programming for finding its solution. Its application to the joint program of beamforming and relay assignment for the case of orthogonal transmission of the users is presented in Section III. Section IV is devoted to the problem of jointly optimized beamforming and relay assignment in nonorthogonal transmission of the users. Simulations are presented in Section V. Section VI ...

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Section: Joint Beamforming and Relay Selection With Orthogonal Tmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Joint Optimization of Cooperative Beamforming and Relay Assignment in Multi-User Wireless Relay Networks

Che

Tuan

Nguyen

2014

IEEE Trans. Wireless Commun.

153

125

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“…14 So far, the power allocation issue has been widely investigated. [15][16][17][18][19] For instance, in the work of Nasri et al, 15 power allocation was studied in consideration of single-source, single-destination cooperative communication systems. Intuitively speaking, the function of power allocation can be formulated quite naturally in multisource cooperative communication systems.…”

Section: Introductionmentioning

confidence: 99%

“…Intuitively speaking, the function of power allocation can be formulated quite naturally in multisource cooperative communication systems. In the work of Fang et al, 16 a joint power allocation and relay selection strategy has been studied in multisource cooperative communication networks, where a distributed power allocation algorithm is proposed based on a time-reversible Markov chain. Furthermore, in the work of Tong et al, 17 power allocation for multihop cooperative communication networks comprising multiple relays has been studied by considering the cooperative AF scheme, which is designed for minimizing the bit error rate and maximizing the sum data rate simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Power allocation for multisource, multidestination cooperative vehicular networks under an outage probability constraint

Zhou

Qiu

Chen

et al. 2019

Trans Emerging Tel Tech

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In multisource, multidestination vehicular networks, vehicles equipped with wireless communication devices are capable of sharing data with each other as well as relaying data using roadside infrastructures. Therefore, low-power wireless communications play a critical role in improving the performance of transportation systems. To substantially reduce the power consumption of the transportation systems, a new power allocation strategy operating with an amplify-and-forward and hybrid decode-amplify-forward (AF-HDAF) protocol is proposed and analyzed. The cooperative manners of the employed relay nodes in the AF-HDAF strategy are manipulated, relying on the smartly designed forward strategies of the cooperative nodes. Furthermore, based on an outage probability constraint, the optimal power allocation that minimizes the sum power consumption is investigated. Numerical results confirm the validity of the proposed theoretical analysis, showing that the performance of the proposed power allocation scheme can be substantially improved by implementing the proposed AF-HDAF protocol.

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“…and environmental pollution have increased enormously [2,3] in smart city communication. The aforementioned issues have attracted the attention of researchers to develop efficient solutions for energy-saving and power control [4][5][6]. Two relay schemes, namely, (i) amplify-and-forward (AF) and (ii) decode-and-forward (DF), have attained significant attentions as the most typical relaying protocols [7].…”

mentioning

confidence: 99%

Robust power optimization scheme for cooperative wireless relay system in smart city

et al. 2016

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Ultra dense deployment of base stations is one of most significant features in smart city communication networks. Aiming at the large-scale wireless communication issue in smart city, we propose a distributed robust power allocation scheme with proportional fairness for cooperative orthogonal frequency-division-multipleaccess relay network. With the amplify-and-forward relay mode, all of the relays assist the information transmission simultaneously on orthogonal subcarriers. Considering the uncertainty of channel gains, first we aim at achieving the maximum utility subject to the constraints of outage probability threshold and power bound. Subsequently, the problem is transformed to a solvable convex optimization problem with determination constraints. The dual-decomposition method is applied to solve the formulated optimization problem. To reduce the information exchange of the whole system, we propose a computationally efficient distributed iteration algorithm. Numerical results reveal the effectiveness of the proposed robust optimization algorithm. INTRODUCTIONWith the rapid advancement and application of communication infrastructure, next generation mobile communication technologies, cloud computing, the internet of things and so on, the concept of smart city has been proposed and developed in recent years. Smart health care, smart transportation, smart buildings, smart homes, smart government, and smart electric grids may form the main parts of future smart cities. The smart city will bring us a more convenient and intelligent life in future. Nevertheless, it is a key problem to the development of smart city that establishes a robust communication network. To guarantee the high-speed communication requirements of the increasing users and the further transmission range, an army of base stations and other communication devices need to be constructed. Meanwhile, the large number of new communication devices not only increases the cost of communication operators but also increases the consumption of energy. Therefore, it is vital to enhance the communication quality and reduce the cost with a new communication technology. Relay-assisted communication plays an important role in extending the transmission range and enhancing the communication quality in wireless networks [1]. Lowpowered and high-capacity communication and transmission have become possible with the help of cooperative relay. With the rapid upsurge in services of cellular networks, energy consumption Apparently, the above Hessian matrix is definite. We conclude that the constraints form a convex feasible set. Therefore, the reformulated problem (P2) is a convex optimization problem.

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Power Allocation for Multiuser Cooperative Communication Networks Under Relay-Selection Degree Bounds

Cited by 10 publications

References 26 publications

Joint Optimization of Cooperative Beamforming and Relay Assignment in Multi-User Wireless Relay Networks

Joint Optimization of Cooperative Beamforming and Relay Assignment in Multi-User Wireless Relay Networks

Power allocation for multisource, multidestination cooperative vehicular networks under an outage probability constraint

Robust power optimization scheme for cooperative wireless relay system in smart city

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