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检索条件"主题词=Concave Programming"

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Energy Efficient Two-way AF Relay System with Multiple-antennas

Energy Efficient Two-way AF Relay System with Multiple-anten...

引用

IEEE 74th Vehicular Technology Conference (VTC)

作者： Kim, Hongjoon Lee, Namjeong Kang, Joonhyuk Korea Adv Inst Sci & Technol KAIST Taejon South Korea

ISBN: (纸本)9781424483273

In this paper, we study an energy efficient two-way amplify-and-forward (AF) relay network equipped with multiple antennas at both sources and relay. To minimize the transmit power while satisfying quality of service (QoS) of both sources, transmit beamformers and receive combiners are designed with ZF-based relay processing matrix. Due to the non-convexity of the optimization problem, the original problem is decomposed into two simpler optimization problems which can be solved through iteration algorithm. As an alternative, eigen-beamforming based technique is also provided to reduce the complexity of the iterative solution at the expense of the power usage. Numerical results show that the proposed solution efficiently reduces the additional power usage of the system compared to the eigen-beamforming based technique while meeting the QoS constraint of each source. Moreover, we can see the proposed algorithm converges to the steady-state value in a reasonable number of iterations.

关键词： Array signal processing Minimization Optimization QoS constraint Quality of service Relays Transceivers Vectors amplify and forward communication amplify-and-forward relay network antennas concave programming eigenbeamforming based technique eigenvalues a

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Linear MMSE Precoding and Equalization for Network MIMO with Partial Cooperation

Linear MMSE Precoding and Equalization for Network MIMO with...

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54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Kaviani, Saeed Simeone, Osvaldo Krzymien, Witold A. Shamai (Shitz), Shlomo Univ Alberta TRLabs Edmonton AB Canada New Jersey Inst Technol CWCSPR Newark NJ 07102 USA Technion Israel Inst Technol Dept Elect Engn Haifa Israel

ISBN: (纸本)9781424492688

A cellular multiple-input multiple-output (MIMO) downlink system is studied in which each base station (BS) transmits to some of the users, so that each user receives its intended signal from a subset of the BSs. This scenario is referred to as network MIMO with partial cooperation, since only a subset of the BSs are able to coordinate their transmission towards any user. The focus of this paper is on the optimization of linear beamforming strategies at the BSs and at the users for network MIMO with partial cooperation. Individual power constraints at the BSs are enforced. It is first shown that the system is equivalent to a MIMO interference channel with generalized linear constraints (MIMO-IFC-GC). The problem of minimizing the weighted sum mean square error (WSMSE) of the data estimates is non-convex, and suboptimal solutions with reasonable complexity need to be devised. Novel designs that aim at minimizing the WSMSE are then proposed. Extensive numerical simulations are provided to compare the performance of the considered schemes for realistic cellular systems.

关键词： Interference channels MIMO MIMO communication MIMO interference channel MMSE equalization Optimization Receiving antennas Transmitters base station cellular multiple input multiple output downlink system cellular radio cellular system concave programming cooperative communication equalisers generalized linear constraints interference (signal) least mean squares methods linear MMSE precoding linear beamforming strategy network MIMO nonconvex problem partial cooperation power constraints precoding radiofrequency interference weighted sum mean square error

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On Using Multi-State Spectrum Sensing for Joint Detection and Transmission in Opportunistic Spectrum Sharing

On Using Multi-State Spectrum Sensing for Joint Detection an...

引用

54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Tsai, Jiun-Shian Hsieh, Hung-Yun Natl Taiwan Univ Grad Inst Commun Engn Taipei 106 Taiwan

ISBN: (纸本)9781424492688

In this paper, we investigate the problem of opportunistic spectrum sharing through joint optimization of spectrum hole detection and transmission power control. Unlike conventional spectrum sensing models that classify the state of the primary user as being idle or active, we consider a multi-state spectrum sensing model where there exist multiple states to be chosen as the detection decision. Different states represent the degrees of certainty at the detector regarding the presence of the primary user, and hence are mapped to different levels of transmission powers to be used by the secondary user for spectrum access. Our goal thus is to jointly decide the optimal detection thresholds and transmission powers such that the achieved capacity at the secondary user is maximized subject to the interference temperature limit constraint at the primary user. We first formulate a non-convex optimization problem based on the system models and then propose an algorithm for solving the problem. By varying the number of states in the multi-state sensing model, we compare the performance of the conventional two-state hard sensing model and the infinite-state soft sensing model and motivate further investigation on multi-state spectrum sensing for dynamic spectrum access.

关键词： Detectors Equations Interference Joints Optimization Transmitters cognitive radio concave programming detection decision dynamic spectrum access infinite-state soft sensing model interference temperature limit constraint joint detection-transmission optimization multistate spectrum sensing model nonconvex optimization problem opportunistic spectrum sharing optimal detection thresholds power control primary user radiofrequency interference secondary user signal detection spectrum hole detection telecommunication control transmission power control two-state hard sensing model

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Optimum Multi-user Detection by Nonsmooth Optimization

Optimum Multi-user Detection by Nonsmooth Optimization

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IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Tuan, H. D. Son, T. T. Tuy, H. Nguyen, H. H. Univ New S Wales Sydney NSW 2071 Australia Toyota Technol Inst Nagoya Aichi 468 Japan Inst Matemat Hanoi 10307 Vietnam Univ Saskatchewan Saskatoon SK Canada

ISBN: (纸本)9781457705397

The optimum multiuser detection (OMD) is a discrete (binary) optimization. The previously developed approaches often relax it by a semi-definite program (SDP) and then employ randomization for searching the optimal solution around the solution of this relaxed SDP. In this paper, we show the limited capacity of this SDP program, which at the end cannot give a better solution than the simple linear minimum mean square error detector (LMMSE). Our departure point is to express the problem as quadratic minimization over quadratic equality constraint (QMQE) or concave quadratic minimization over a box of continuous optimization (CQOB). The QMQE allows us to develop a nonsmooth optimization algorithm to locate the global optimal solution of OMD, while CQOB facilities effective confirmation of the solutions found by QMQE. Our intensive simulation clearly shows that the algorithm outperforms all previously developed algorithms while the computational burden is essentially reduced.

关键词： Multiuser detection semi-definite programming concave programming nonsmooth optimization

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Polytope of Correct (Linear programming) Decoding and Low-Weight Pseudo-Codewords

Polytope of Correct (Linear Programming) Decoding and Low-We...

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IEEE International Symposium on Information Theory (ISIT)

作者： Chertkov, Michael Stepanov, Mikhail LANL CNLS Los Alamos NM 87545 USA Univ Kaiserslautern Dept Math D-67663 Kaiserslautern Germany

ISBN: (纸本)9781457705953

We analyze Linear programming (LP) decoding of graphical binary codes operating over soft-output, symmetric and log-concave channels. We show that the error-surface, separating domain of the correct decoding from domain of the erroneous decoding, is a polytope. We formulate the problem of finding the lowest-weight pseudo-codeword as a non-convex optimization (maximization of a convex function) over a polytope, with the cost function defined by the channel and the polytope defined by the structure of the code. This formulation suggests new provably convergent heuristics for finding the lowest weight pseudo-codewords improving in quality upon previously discussed. The algorithm performance is tested on the example of the Tanner [155,64,20] code over the Additive White Gaussian Noise (AWGN) channel.

关键词： AWGN channel AWGN channels AWGN channels Convex functions Decoding LP decoding Minimization Noise Optimization Parity check codes additive white gaussian noise channel binary codes channel coding concave programming convergent heuristic correct decoding cost function decoding erroneous decoding error correction codes error-surface separating domain graphical binary code linear programming linear programming decoding log-concave channel lowest-weight pseudo-codeword nonconvex optimization polytope soft-output channel symmetric channel

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Low Complexity Semi-Blind Channel Estimation Algorithm in Two-Way Relay Networks

Low Complexity Semi-Blind Channel Estimation Algorithm in Tw...

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22nd IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Zhao, Qiong Zhou, Zhendong Vucetic, Branka Univ Sydney Sch Elect & Informat Engn Sydney NSW 2006 Australia

ISBN: (纸本)9781457713484

In this work, we propose a low complexity semi-blind channel estimation algorithm, referred to as the variance squared maximum likelihood (VSML) estimator, which employs only one training symbol in each channel estimation, to estimate general non-reciprocal flat-fading channels in amplify-and forward (AF) two-way relay networks (TWRNs). We formulate a non-convex objective function and obtain closed-form channel estimates by minimizing its approximate expression. Theoretical analysis proves that the derived channel estimation is asymptotically optimal in large sample size scenarios. Monte-Carlo simulation results show that the VSML estimator outperforms the existing relaxed maximum likelihood (RML) estimator in terms of mean squared error (MSE) performance and remarkably reduces the computational complexity by completely avoiding the grid-search algorithm under M-ary phase-shift-keying (MPSK) modulation.

关键词： Channel estimation M-ary phase-shift-keying MPSK modulation MSE performance Maximum likelihood estimation Monte Carlo methods Monte-Carlo simulation Phase shift keying Relays Signal to noise ratio Training VSML estimator amplify and forward communication amplify-and-forward two-way relay networks channel estimation closed-form channel estimation computational complexity computational complexity concave programming fading channels grid-search algorithm low complexity semiblind channel estimation algorithm maximum likelihood estimation mean square error methods mean squared error performance nonconvex objective function nonreciprocal flat-fading channel estimation phase shift keying training symbol variance squared maximum likelihood estimator

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Optimized Solutions for Beamforming Problems in Amplify-Forward Wireless Relay Networks

Optimized Solutions for Beamforming Problems in Amplify-Forw...

引用

54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Phan, A. H. Tuan, H. D. Kha, H. H. Univ New South Wales Sch EET Sydney NSW 2052 Australia Univ Technol Sch Informat Technol & Engn Sydney NSW Australia

ISBN: (纸本)9781424492688

Beamforming problems in amlify-forward (AF) wireless relay network can be formulated as nonconvex quadratically constrained quadratic programming (QCQP) problems which is very difficult to solve directly. Generally, by transforming a QCQP problem into a semi-definite program (SDP) and by relaxing rank-one constraints, the problem can be tackled essentially. If resulting matrices found after solving SDP problems are of rank-one then the task can be terminated. However, in some scenarios such as minimizing individual power constraints on relays, most of the rank-one dropped SDP solutions have rank higher than one. In this case, a nonsmooth reverse convex optimization technique is employed to solve the problem iteratively then rank-one solutions can be optimized numerically.

关键词： Array signal processing Interference Optimization Receivers Relays Vectors Wireless communication amplify and forward communication amplify-forward wireless relay networks beamforming problem concave programming convex programming nonconvex quadratically constrained quadratic programming problem nonsmooth reverse convex optimization power constraint quadratic programming radio networks semidefinite program

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Towards a Fair Non-convex Resource Allocation in Wireless Networks

Towards a Fair Non-convex Resource Allocation in Wireless Ne...

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22nd IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Tychogiorgos, G. Gkelias, A. Leung, K. K. Univ London Imperial Coll Sci Technol & Med London SW7 2AZ England

ISBN: (纸本)9781457713484

This paper presents a non-convex optimization framework for the Network Utility Maximization problem in Wireless Networks, which incorporates the interference among links and introduces a power penalty term in the objective function to assure both convergence and energy efficiency of the method. Moreover, a distributed gradient based algorithm is proposed that converges to the optimal solution for problems with zero duality gap and a fair-allocation heuristic is presented to resolve user oscillations when they occur. Finally, numerical results regarding the performance of the heuristic and the distributed approach are presented.

关键词： Convergence Distributed algorithms Optimization Oscillators Resource management Vectors Wireless communication concave programming convergence distributed gradient based algorithm energy conservation energy efficiency fair nonconvex resource allocation fair-allocation heuristic gradient methods network utility maximization problem nonconvex optimization framework objective function power penalty term radio networks resource allocation wireless networks zero duality gap

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OPTIMAL RESOURCE ALLOCATION IN OFDMA DOWNLINK SYSTEMS WITH IMPERFECT CSI

OPTIMAL RESOURCE ALLOCATION IN OFDMA DOWNLINK SYSTEMS WITH I...

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12th IEEE International Workshop on Signal Processing Advances in Wireless Communications

作者： Aggarwal, Rohit Assaad, Mohamad Koksal, C. Emre Schniter, Philip Ohio State Univ Dept ECE Columbus OH 43210 USA Supelac Dept Telecom Gif Sur Yvette France

ISBN: (纸本)9781424493326

In this paper, we address the problem of joint scheduling and resource allocation in the downlink of an orthogonal frequency division multiple access (OFDMA)-based wireless network when the per-user SNR is known only in distribution. In particular, we consider sum-utility maximization over user schedules, powers, and code rates, subject to an instantaneous sum-power constraint. We consider both a "continuous" scenario where, during a time-slot, each OFDMA subchannel can be time-shared among multiple users and/or code rates, and a "discrete" scenario where no time-sharing is allowed. For the non-convex optimization problem arising in the continuous case, we propose an efficient exact solution. For the mixed-integer optimization problem arising in the discrete case, we propose a polynomial-complexity approximate solution and derive a bound on its optimality gap. We also provide a numerical study of goodput maximization for the SNR distribution that results from the use of pilot-aided MMSE channel estimation.

关键词： Channel estimation Downlink MMSE channel estimation OFDM OFDM modulation OFDMA downlink system OFDMA-based wireless network Optimization Resource management SNR distribution Signal to noise ratio Tin channel estimation concave programming frequency division multiple access integer programming least mean squares methods mixed integer optimization nonconvex optimization optimal resource allocation optimality gap orthogonal frequency division multiple access polynomial-complexity approximation radio networks resource allocation sum-utility maximization

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Power Efficient Resource Allocation in Uplink SC-FDMA Systems

Power Efficient Resource Allocation in Uplink SC-FDMA System...

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22nd IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Ahmad, Ayaz Assaad, Mohamad SUPELEC Dept Telecommun F-91192 Gif Sur Yvette France

ISBN: (纸本)9781457713484

In this paper, we study sum-power minimization problem in SC-FDMA which is adopted as the multiple access scheme for uplink in the 3GPP-LTE standard. Unlike OFDMA, in addition to the restriction of allocating a sub-channel to one user at most, the multiple sub-channels allocated to a user in SC-FDMA should be consecutive as well. This renders the resource allocation problem prohibitively difficult and the standard optimization tools (e.g., Lagrange dual approach widely used for OFDMA, etc.) can not help towards its optimal solution. We propose a novel polynomial-complexity optimization framework that is inspired from the recently developed canonical duality theory. We first formulate the resource allocation problem as a binary-integer programming (BIP) problem and then transform the BIP problem into a continuous space canonical dual problem which is a concave maximization problem under certain conditions. Based on the solution of the canonical dual problem, we derive a joint power and sub-channels allocation algorithm that has polynomial complexity. We provide conditions under which the proposed algorithm is optimal. The proposed framework is illustrated through simulations where the results show that the proposed algorithm improves the system performance significantly.

关键词： 3G mobile communication 3GPP-LTE standard BIP problem Complexity theory Fading Frequency division multiaccess Long Term Evolution OFDMA Optimization Resource management Signal to noise ratio Transforms binary-integer programming problem concave maximization problem concave programming continuous space canonical dual problem frequency division multiple access integer programming minimisation multiple access scheme optimization tools polynomial-complexity optimization framework power efficient resource allocation subchannel allocation algorithm sum-power minimization problem uplink SC-FDMA systems wireless channels

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