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检索条件"主题词=Concave Programming"

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Pricing for Demand Shaping and Proactive Download in Smart Data Networks

Pricing for Demand Shaping and Proactive Download in Smart D...

引用

32nd IEEE INFOCOM Conference

作者： Tadrous, John Eryilmaz, Atilla El Gamal, Hesham Ohio State Univ Dept Elect & Comp Engn Columbus OH 43210 USA

ISBN: (纸本)9781467359467

We address the question of optimal proactive service and demand shaping for content distribution in data networks through smart pricing. We develop a proactive download scheme that utilizes the probabilistic predictability of the human demand by proactively serving potential users' future requests during the off-peak times. Thus, it smooths-out the network traffic and minimizes the time average cost of service. Moreover, we incorporate the varying economic responsiveness and demand flexibilities of users into our model to develop a demand shaping mechanism that further improves the gains of proactive downloads. To that end, we propose a model that captures the uncertainty about the users' demand as well as their responsiveness to the pricing employed by the service providers. We propose a joint proactive resource allocation and demand shaping scheme based on non-convex optimization algorithms, and show that it always leads to strictly better performance over its proactive counterpart without demand shaping.

关键词： computer networks concave programming packet radio networks pricing probability resource allocation telecommunication services telecommunication traffic

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Design of Sensing and Power Allocation Strategies For Energy-Aware Multi-Channel Cognitive Radio Networks

Design of Sensing and Power Allocation Strategies For Energy...

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IEEE International Symposium on Dynamic Spectrum Access Networks

作者： Huang, Guangjie Tugnait, Jitendra K. Auburn Univ Dept Elect & Comp Engn Auburn AL 36849 USA

ISBN: (纸本)9781467344487;9781467344470

Frequency spectrum and energy are two key resources of green cognitive radio networks with battery-powered wireless terminals. The issues of how to utilize sparse frequency spectrum and limited energy resource pose challenges to the design of sensing and power allocation strategies that affect both throughput and energy consumption. In this paper, we first construct an utility function that incorporates throughput as reward and energy consumption as cost for a time slotted multi-channel cognitive radio network. An optimization problem to maximize the utility function is formulated involving optimization of both sensing parameters (sensing duration and local test threshold) and power allocation strategy. The problem is non-convex, however, we decouple it into two separate convex problems and propose an iterative algorithm to obtain a suboptimal solution. The simulation results show that our iterative algorithm converges fast and performs better than an "only power allocation optimization" approach and an existing approach that ignores energy efficiency.

关键词： channel allocation cognitive radio concave programming convex programming iterative methods radio networks radio spectrum management

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LIFETIME MAXIMIZATION IN DISTRIBUTED SENSOR NETWORK WITH EVENT-TRIGGERED ADAPTIVE FILTERING

LIFETIME MAXIMIZATION IN DISTRIBUTED SENSOR NETWORK WITH EVE...

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46th Asilomar Conference on Signals, Systems and Computers

作者： Malipatil, Amaresh V. Huang, Yih-Fang Univ Notre Dame Dept Elect Engn Notre Dame IN 46556 USA

ISBN: (纸本)9781467350518

This paper considers the problem of maximizing the lifetime of a wireless sensor network (WSN) that is deployed to track a parameter vector, subject to a mean-squared-deviation (MSD) constraint. We employ an event-triggered approach using the set-membership normalized least mean-squared (SM-NLMS) adaptive filter in each node wherein the parameter estimate is updated, and hence transmitted to a fusion node (FN), only when the estimation error exceeds a predefined threshold, which is defined to be a triggering event. This problem of maximizing network lifetime (NLT) is posed as an optimization problem which turns out to be non-convex. We propose a suboptimal iterative solution for this problem and show through simulations that the NLT is enhanced significantly compared to a time-triggered approach such as NLMS.

关键词： adaptive filters concave programming estimation theory least mean squares methods parameter estimation wireless sensor networks

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Linear Precoding Designs for Amplify-and-Forward Multiuser Two-Way Relay Systems

Linear Precoding Designs for Amplify-and-Forward Multiuser T...

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54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Wang, Rui Tao, Meixia Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China

ISBN: (纸本)9781424492688

We investigate the linear precoding designs for multiuser two-way relay system (MU-TWRS) where a multi-antenna base-station (BS) communicates with multiple single-antenna mobile stations (MSs) via a multi-antenna relay station (RS). The amplify-and-forward (AF) relay protocol is employed. The design goal is to optimize the precodings at BS, RS or both so as to minimize the total mean-square error (MSE) of the uplink messages while maintaining the individual signal-to-interference-plus-noise ratio (SINR) requirement for each downlink signal. We show that the BS precoding design problem can be converted to a standard second order cone programming (SOCP), while the RS precoding is non-convex for which a local optimal solution is obtained using an iterative algorithm. A joint BS-RS precoding is also obtained by alternating optimization of BS precoding and RS precoding with guaranteed convergence. Numerical results show that RS-precoding is superior to BS-precoding. Furthermore, the joint BS-RS precoding can significantly outperform the two individual precoding schemes. The implementation issues including complexity and feedback overhead are also discussed.

关键词： BS-precoding Downlink Interference Joints Optimization RS-precoding Relays Signal to noise ratio Vectors amplify and forward communication amplify and forward protocol concave programming cone programming interference suppression iterative algorithm iterative methods linear codes linear precoding design mean square error method mean square error methods mobile stations multi-antenna base station multi-antenna relay station multifrequency antennas multiuser channels multiuser two-way relay system nonconvex programming optimization precoding protocols signal to interference plus noise ratio uplink messages

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Low-Rank Solution of Convex Relaxation for Optimal Power Flow Problem

Low-Rank Solution of Convex Relaxation for Optimal Power Flo...

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IEEE International Conference on Smart Grid Communications (SmartGridComm)

作者： Sojoudi, Somayeh Madani, Ramtin Lavaei, Javad CALTECH Dept Comp & Math Sci Pasadena CA 91125 USA Columbia Univ Dept Elect Engn Columbia MO USA

ISBN: (纸本)9781479915262

This paper is concerned with solving the nonconvex problem of optimal power flow (OPF) via a convex relaxation based on semidefinite programming (SOP). We have recently shown that the SOP relaxation has a rank-l solution from which the global solution of OPF can be found, provided the power network has no cycle. The present paper aims to provide a better understating of the SOP relaxation for cyclic networks. To this end, an upper bound is derived on rank of the minimum-rank solution of the SOP relaxation, which depends only on the topology of the power network. This bound is expected to be very small in practice due to the mostly planar structure of real-world networks. A heuristic method is then proposed to enforce the low-rank solution of the SOP relaxation to become rank-1. To elucidate the efficacy of this technique, it is proved that this method works for weakly-cyclic networks with cycles of size 3. Although this paper mainly focuses on OPF, the results developed here can be applied to several OPF-based emerging optimizations for future electrical grids.

关键词： concave programming convex programming load flow power grids relaxation theory

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Single-tone Spectrum Allocation under SINR Requirements

Single-tone Spectrum Allocation under SINR Requirements

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IEEE International Symposium on Dynamic Spectrum Access Networks

作者： Ellingsaeter, Brage Univ Oslo UNIK Univ Grad Ctr Kjeller N-0316 Oslo Norway

ISBN: (纸本)9781467344487;9781467344470

In this paper we investigate the problem of allocating spectrum among radio nodes under SINR requirements. This problem is of special interest in dynamic spectrum access networks where topology and spectral resources differ with time and location. The problem is to determine the number of radio nodes that can transmit simultaneously while still achieving their SINR requirements and then decide which channels these nodes should transmit on. Previous work have shown how this can be done for a large spectrum pool where nodes allocate multiple channels from that pool which renders a linear programming approach feasible when the pool is large enough. In this paper we extend their work by considering arbitrary individual pool sizes and allow nodes to only transmit on one channel. Due to the accumulative nature of interference this problem is a non-convex integer problem which is NP-hard. However, we introduce a constraint transformation that transforms the problem to a binary quadratic constraint problem. Although this problem is still NP-hard, well known heuristic algorithms for solving this problem are known in the literature. We implement a heuristic algorithm which yields both good solutions and can be implemented in a distributed manner. Simulation results show that this approach provides solutions within an average gap of 10% of solutions obtained by a genetic algorithm for the original non-convex integer problem.

关键词： channel allocation cognitive radio concave programming genetic algorithms interference suppression linear programming quadratic programming radio access networks radio spectrum management telecommunication network topology

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Global Design of Perfect-Reconstruction Orthogonal Cosine-Modulated Filter Banks

Global Design of Perfect-Reconstruction Orthogonal Cosine-Mo...

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23rd Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： Yan, Jie Lu, Wu-Sheng Univ Victoria Dept Elect & Comp Engn Victoria BC V8W 3P6 Canada

ISBN: (纸本)9781424453771

Designing perfect-reconstruction orthogonal cosine-modulated filter banks is essentially a nonconvex problem and to date only local solutions can be claimed. By virtue of the recent progress in global polynomial optimization, this paper describes an attempt of developing a global design method using an order-recursive strategy combined with a technique that identifies a desirable initial point in each round of recursion. Simulation and comparison studies are presented to evaluate the performance of the proposed design technique.

关键词： channel bank filters concave programming design technique global design method global polynomial optimization modulation nonconvex problem order-recursive strategy perfect-reconstruction orthogonal cosine-modulated filter banks performance evaluation performance evaluation polynomial approximation recursive estimation

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Co-Primary Spectrum Sharing with Resource Allocation in Small Cell Network 1

Co-Primary Spectrum Sharing with Resource Allocation in Smal...

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1st International Conference on 5G for Ubiquitous Connectivity (5GU)

作者： Sanguanpuak, Tachporn Rajatheva, Nandana Latva-Aho, Matti Asian Inst Technol Dept Telecommun Commun Engn Klong Lunag Pathumthani Thailand Univ Oulu Dept Commun Engn FI-90014 Oulu Finland

ISBN: (纸本)9781631900556

We study co-primary spectrum sharing concept in small cell multiuser networks. Downlink transmission is considered with Rayleigh fading in interfering broadcast channel. Multiple-input-single-output ( MISO) system is considered in two small cells. The sum rate maximization problem is studied in two cells having multiple users with multiple subcarriers. Zeroforcing ( ZF) precoders are considered at both base stations. The problem becomes non-convex then and we factor the main objective problem into two subproblems. First subproblem is multiuser with subcarriers allocation where we assume that each subcarrier can be allocated to multiple users. Gale-Shapley algorithm is proposed for subcarrier allocation problem. Second subproblem is where ZF precoders are employed at both base stations for allocating power. It leads to water-filling based power allocation for both base stations.

关键词： Rayleigh channels cellular radio concave programming radio spectrum management radiofrequency interference resource allocation Gale-Shapley algorithm MISO system Rayleigh fading broadcast channel interference coprimary spectrum sharing concept downlink transmission multiple-input-single-output system nonconvex problem power allocation small cell multiuser networks subcarrier allocation problem sum rate maximization problem water-filling based power allocation zero-forcing precoders Signal to noise ratio Resource utilization downlinking Radio spectrum management Rayleigh fading signal to noise ratios power splitting management of resources Radiofrequency interference Raleigh fading channels cellular radio Subcarriers BASE STATION single input single output systems

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Resource Allocation and Scheduling in Multi-Cell OFDMA Decode-and-Forward Relaying Networks

Resource Allocation and Scheduling in Multi-Cell OFDMA Decod...

引用

IEEE Global Telecommunications Conference (GLOBECOM 2010)

作者： Ng, Derrick Wing Kwan Schober, Robert Univ British Columbia Vancouver BC V5Z 1M9 Canada

ISBN: (纸本)9781424456383

In this paper, we formulate a joint optimization problem for resource allocation and scheduling in multi-cell orthogonal frequency division multiple access (OFDMA) half-duplex decode-and-forward (DF) relay assisted networks. Our problem formulation takes into account multi-cell interference and heterogeneous data rate requirements. We transform the resulting non-convex and combinatorial optimization problem into a standard convex optimization problem by introducing an additional interference constraint, which constitutes a performance lower bound for the original problem. Subsequently, the transformed optimization problem is solved by using dual decomposition and a centralized iterative resource allocation algorithm with closed-form power and subcarrier allocation policies is derived maximizing the average weighted system throughput (bit/s/Hz/base station). Simulation results illustrate that our proposed algorithm approaches the maximum achievable throughput and provides substantial performance gains compared to single-cell optimization.

关键词： OFDM modulation OFDMA closed-form power combinatorial mathematics combinatorial optimization concave programming decode and forward communication frequency division multiple access half-duplex decode-and-forward relay assisted network heterogeneous data r

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Optimal Transmission over a Fading Channel with Imperfect Channel State Information

Optimal Transmission over a Fading Channel with Imperfect Ch...

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54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Hu, Yichuan Ribeiro, Alejandro Univ Penn Dept Elect & Syst Engn Philadelphia PA 19104 USA

ISBN: (纸本)9781424492688

This paper considers a wireless channel when the probability distribution of fading is unknown and the transmitter has access to imperfect channel state information (CSI). Transmitted power and coding mode are adapted to the available imperfect CSI through the use of a backoff function in order to maximize the expected transmission rate subject to an average power constraint. Determination of the optimal power allocation and backoff function is a non-convex stochastic optimization problem with infinitely many variables. Despite its non-convexity, the duality gap of this problem has been shown to be null. Exploiting this property, we show that the optimal power allocation and channel backoff functions are uniquely determined by the optimal dual variable. This affords considerable simplification because the dual optimization problem is convex and one-dimensional - whereas the original primal problem is non-convex and infinite-dimensional. Iterative algorithms that find the optimal power and backoff function based on imperfect CSI without having access to the channel probability distribution are further developed. Numerical results are provided to corroborate theoretical findings.

关键词： Ad hoc networks CSI Channel estimation Fading Optimization Resource management Transmitters Wireless communication average power constraint channel coding channel probability distribution coding mode concave programming dual optimization problem fading channel fading channels imperfect channel state information iterative algorithms iterative methods nonconvex stochastic optimization problem optimal power allocation optimal transmission stochastic programming wireless channel

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