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Optimal channel-aware ALOHA protocol for random access in WLANs with multipacket reception and decentralized channel state information

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2008年第6期56卷 2575-2588页

作者： Ngo, Minh Hanh Krishnamurthy, Vikram Tong, Lang Univ British Columbia Dept Elect & Comp Engn Vancouver BC V6T 1Z4 Canada Cornell Univ Sch Elect & Comp Engn Ithaca NY 14853 USA

Perfect decentralized channel state information (CSI) is utilized to design an optimal distributed medium access control (MAC) protocol for wireless local area networks (WLANs) with the multipacket reception capability, which is available in CDMA systems for example. In particular, we consider the scenario where a finite number of users transmit packets to a common access point via a channel-aware ALOHA protocol. We analyze the structure of the optimal channel-aware transmission policies for both the spatially homogeneous WLAN system model, where users deploy identical transmission policies, and the spatially heterogeneous WLAN system model, where users are allowed to deploy different transmission policies. It is shown that the optimal transmission policy is nonrandomized and piecewise continuous with respect to the channel state. Furthermore, we prove for CDMA systems, which represent the most important example of networks with the MPR capability, that under a suitable condition, there exists a channel state threshold beyond which it is optimal not to transmit. Last, we propose a provably convergent stochastic approximation algorithm for estimating the optimal transmission policy for spatially homogeneous networked users. Numerical studies illustrate the performance of the algorithm and the degenerate, nonrandomized structure of the optimal transmission policy.

关键词： channel state information gradient estimation multipacket reception optimal transmit policy stochastic gradient algorithms wireless local area network

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Block-Shanno MBER Algorithm in a Spatial Multiuser MIMO/OFDM

Block-Shanno MBER Algorithm in a Spatial Multiuser MIMO/OFDM

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14th European Wireless Conference

作者： Samir, Tamer A. Elnoubi, Said Elnashar, Ayman Etihad Etisalat Riyadh Saudi Arabia Univ Alexandria Alexandira Egypt

ISBN: (纸本)9781424431205

In this paper, we deploy a modified version of Shanno algorithm in order to optimize the bit error rate (BER) cost function using a nonlinear block optimization strategy for its minimization. The resulting algorithm is called the Block Shanno Mnimum BER (BSMBER), which is conducted in the design of spatial multiuser receivers for orthogonal frequency division multiplexing (OFDM) system using multiple antennas at the transmitter and receivers. Adaptive resource managements are considered assuming instantaneous channel knowledge. Simulation analyses show the enhancements in convergence rate and BER performance of the proposed BSMBER over the minimum mean squared error (MMSE) and other minimum BER (MBER) based algorithms. In addition, BSMBER has faster convergence rate over the gradient Newton algorithms but loses some performance enhancements in the sense of the BER steady states while maintaining linearity in complexity.

关键词： MUD OFDM MIMO BER MMSE stochastic gradient algorithms

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Robust failure compensation for a morphing aircraft model using a probabilistic approach

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IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY 2007年第2期15卷 324-331页

作者： Ataei-Esfahani, Armin Wang, Qian Penn State Univ Mech & Nucl Engn Dept University Pk PA 16802 USA

We present a probabilistic robust control design for a morphing aircraft model subject to uncertain actuator failure. The morphing aircraft model has multiple distributed arrays of shape-change devices that are used to generate moments for stabilization and low-rate maneuvering, augmenting conventional control surfaces. Each actuator operates at either on or off state;failure of each actuator could cause uncertainty in the applied control input. We characterize the morphing aircraft's actuation failure in a probabilistic way. In particular, each shape-change device within an actuator array is assumed to have certain probability to fail While devices from different arrays may have different failure probabilities. Consequently, we model the uncertain actuator failure as a random parametric uncertainty in the input matrix of the morphing aircraft model. A probabilistic robust explicit-model-following controller is then designed to stabilize the closed-loop system and to satisfy tracking performance subject to uncertain actuator failure. Simulation results are presented and evaluated for the application of this probabilistic robust failure compensation design to lateral dynamics of an Innovative Control, Effector morphing aircraft model.

关键词： failure compensation morphing aircraft probabilistic robust control quadratic stability shape-change device arrays stochastic gradient algorithms

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Class of minimum bit error rate algorithms

Class of minimum bit error rate algorithms

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9th International Conference on Advanced Communication Technology (ICACT 2007)

作者： Samir, Tamer A. Elnoubi, Said Elnashar, Ayman Network Dev MND Dept Riyadh Saudi Arabia Univ Alexandria Dept Elect Engn Alexandria Egypt

ISBN: (纸本)9788955191318

A class of adaptive beamforming algorithms was proposed based on directly minimizing the bit-error rate (BER). The popular linear minimum bit error rate (MBER) stochastic beamforming algorithms suffer from low convergence speed and large training data. In this paper, we investigate the use of adaptive stochastic gradient-Newton Normalized MBER algorithms in the design of linear beamformer receivers for multipath Rayleigh fading DS-CDMA systems. Simulation analyses show the enhancements in convergence rate and BER performance of the proposed algorithms over the popular minimum mean squared error (MMSE) and other MBER based algorithms in the cost of complexity.

关键词： adaptive beamforming BER MNISE stochastic gradient algorithms Rayleigh fading DS-CDMA

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A simple gradient sign algorithm for transmit antenna weight adaptation with feedback

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2003年第5期51卷 1156-1171页

作者： Banister, BC Zeidler, JR Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 92093 USA Space & Navel Warfare Syst Ctr San Diego CA USA

In this paper, a simple algorithm for adaptation of the complex baseband weights of a transmit antenna array using feedback from the receiver is proposed and analyzed. The system utilizes stochastic gradient adaptation to maximize the power delivered to the receiver for a constrained transmission power, which provides both fading diversity and beam steering gain. Dual perturbed transmission weight vectors are time multiplexed onto the pilot signal, and the receiver generates feedback selecting the perturbed weight vector which delivers greater power. This feedback is used to provide weight adaptation at the transmitter, and this adaptation is shown to be an update by a coarse estimate of the gradient of the delivered power. The performance of the algorithm is analyzed in terms of convergence and tracking of an AR1 fading channel, with simulations confirming the analysis. Bit error rate (BER) simulations in a dynamic fading channel show that the algorithm outperforms previously proposed vector selection feedback, and in slower fading, the algorithm substantially outperforms diversity space time coding.

关键词： adaptive beamforming antenna array stochastic gradient algorithms transmit beamforming

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Adaptive minimum-BER linear multiuser detection for DS-CDMA signals in multipath channels

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2001年第6期49卷 1240-1247页

作者： Chen, S Samingan, AK Mulgrew, B Hanzo, L Univ Southampton Dept Elect & Comp Sci Southampton SO9 5NH Hants England Univ Edinburgh Dept Elect & Elect Engn Edinburgh EH8 9YL Midlothian Scotland

The problem of constructing adaptive minimum bit error rate (MBER) linear multiuser detectors is considered for direct-sequence code division multiple access (DS-CDMA) signals transmitted through multipath channels. Based on the approach of kernel density estimation for approximating the bit error rate (BER) from training data, a least mean squares (LMS) style stochastic gradient adaptive algorithm is developed for training linear multiuser detectors, Computer simulation is used to study the convergence speed and steady-state BER misadjustment of this adaptive MBER linear multiuser detector, and the results show that it outperforms an existing LMS-style adaptive MBER algorithm first presented at Globecom '98 by Yeh et al.

关键词： adaptive algorithms linear multiuser detectors minimum bit error rate minimum mean square error stochastic gradient algorithms

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A TREE-STRUCTURED PIECEWISE-LINEAR ADAPTIVE FILTER

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IEEE TRANSACTIONS ON INFORMATION THEORY 1993年第6期39卷 1907-1922页

作者： GELFAND, SB RAVISHANKAR, CS COMSAT CORP DEPT VOICEBAND PROCCLARKSBURGMD 20871

We propose and analyze a new architecture for nonlinear adaptive filters. These nonlinear filters are piecewise linear filters obtained by arranging linear filters and thresholds in a tree structure. A training algorithm is used to adaptively update the filter coefficients and thresholds at the nodes of the tree, and to prune the tree. The resulting tree-structured piecewise linear adaptive filter inherits the robust estimation and fast adaptation of linear adaptive filters, along with the approximation and model-fitting properties of tree-structured regression models. A rigorous analysis of the training algorithm for the tree-structured filter is performed. Here, some new techniques are developed for analyzing hierarchically organized stochastic gradient algorithms with fixed gains and nonstationary dependent data. Simulation results show the significant advantages of the tree-structured piecewise linear filter over linear and polynomial filters for adaptive echo cancellation.

关键词： ADAPTIVE FILTERING NONLINEAR FILTERING TREE-STRUCTURED METHODS stochastic gradient algorithms DEPENDENT DATA PENALTY METHODS CONVERGENCE ANALYSIS ORDER ANALYSIS ECHO CANCELLATION

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METROPOLIS-TYPE ANNEALING algorithms FOR GLOBAL OPTIMIZATION IN RD

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SIAM JOURNAL ON CONTROL AND OPTIMIZATION 1993年第1期31卷 111-131页

作者： GELFAND, SB MITTER, SK MIT DEPT ELECT ENGN & COMP SCICAMBRIDGEMA 02139 MIT INFORMAT & DECIS SYST LABCAMBRIDGEMA 02139

The convergence of a class of Metropolis-type Markov-chain annealing algorithms for global optimization of a smooth function U(.) on R(d) is established. No prior information is assumed as to what bounded region contains a global minimum. The analysis contained herein is based on writing the Metropolis-type algorithm in the form of a recursive stochastic algorithm X(k+1) = X(k) - a(k)(del U(X(k)) + xi(k)) + b(k)W(k), where {W(k)} is a standard white Gaussian sequence, {xi(k)} are random variables, and a(k) = A/k, b(k) = square-root B/square-root k log log k for k large. Convergence results for (X(k)} are then applied from our previous work [SIAM Journal on Control and Optimization, 29 (1991), pp. 999-1018]. Since the analysis of {X(k)} is based on the asymptotic behavior of the related Langevin-type Markov diffusion annealing algorithm dY(t) = -del U (Y(t)) dt + c(t) dW(t), where W(.) is a standard Wiener process and c(t) = square-root C/square-root log t for t large, this work demonstrates and exploits the close relationship between the Markov chain and diffusion versions of simulated annealing.

关键词： GLOBAL OPTIMIZATION RANDOM OPTIMIZATION SIMULATED ANNEALING stochastic gradient algorithms MARKOV CHAINS

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RECURSIVE stochastic algorithms FOR GLOBAL OPTIMIZATION IN RD

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SIAM JOURNAL ON CONTROL AND OPTIMIZATION 1991年第5期29卷 999-1018页

作者： GELFAND, SB MITTER, SK MIT DEPT ELECT ENGN & COMP SCICAMBRIDGEMA 02139 MIT INFORMAT & DECIS SYST LABCAMBRIDGEMA 02139

An algorithm of the form X(k+1) = X(k) - a(k)(nabla U(X(k) + xi-k) + b(k) W(k), where U(.) is a smooth function on R(d), {xi-k} is a sequence of R(d)-valued random variables, {W(k)} is a sequence of independent standard d-dimensional Gaussian random variables, a(k) = A/k and b(k) = square-root B/ square-root k log log k for k large, is considered. An algorithm of this type arises by adding slowly decreasing white Gaussian noise to a stochastic gradient algorithm. It is shown, under suitable conditions on U(.), {xi-k}, A, and B, that X(k) converges in probability to the set of global minima of U(.). No prior information is assumed as to what bounded region contains a global minimum. The analysis is based on the asymptotic behavior of the related diffusion process dY(t) = -nabla U(Y(t))dt + c(t)dW(t), where W(.) is a standard d-dimensional Wiener process and c(t) = square-root C/square-root log t for t large.

关键词： GLOBAL OPTIMIZATION RANDOM OPTIMIZATION SIMULATED ANNEALING stochastic gradient algorithms DIFFUSIONS

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