Isbn: 9786209373121 - robust time-invariant filtering for wireless relay optimization: a robust time-invariant filtering scheme for performance boost in wireless relay networks (11 risultati)

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New.

Condizione: New.

Taschenbuch. Condizione: Neu. Robust Time-Invariant Filtering for Wireless Relay Optimization | A Robust Time-Invariant Filtering Scheme for Performance Boost in Wireless Relay Networks | Arjun Nichal | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786209373121 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.…

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 52 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents the design, implementation, and performance evaluation of an Adaptive Joint SCAMP Filter and Relay Weight Optimization Scheme for a wireless Amplify-and-Forward (AF) cooperative relay network operating over frequency-selective fading channels. Conventional AF systems suffer from compounded noise and Inter-Symbol Interference (ISI) due to cascaded multi-tap channel effects. To address these limitations, this work employs a Joint Adaptive Filtering approach that simultaneously optimizes the source pre-coding filter and the relay amplification weight to minimize the end-to-end Mean Squared Error (MSE) and enhance the achievable data rate.The joint optimization problem is solved using the Projected Subgradient Method (PSGM), which provides robustness against non-linear constraints such as sparsity while maintaining low computational complexity. The algorithm is implemented and tested in a MATLAB simulation environment under a time-varying Auto-Regressive (AR(1)) fading model. Key performance metrics such as MSE convergence, filter characteristics, achievable rate, and robustness to parameter variations are analyzed.…

Condizione: New. Print on Demand.

Condizione: New. PRINT ON DEMAND.

Paperback. Condizione: new. Paperback. This book presents the design, implementation, and performance evaluation of an Adaptive Joint SCAMP Filter and Relay Weight Optimization Scheme for a wireless Amplify-and-Forward (AF) cooperative relay network operating over frequency-selective fading channels. Conventional AF systems suffer from compounded noise and Inter-Symbol Interference (ISI) due to cascaded multi-tap channel effects. To address these limitations, this work employs a Joint Adaptive Filtering approach that simultaneously optimizes the source pre-coding filter and the relay amplification weight to minimize the end-to-end Mean Squared Error (MSE) and enhance the achievable data rate.The joint optimization problem is solved using the Projected Subgradient Method (PSGM), which provides robustness against non-linear constraints such as sparsity while maintaining low computational complexity. The algorithm is implemented and tested in a MATLAB simulation environment under a time-varying Auto-Regressive (AR(1)) fading model. Key performance metrics such as MSE convergence, filter characteristics, achievable rate, and robustness to parameter variations are analyzed. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents the design, implementation, and performance evaluation of an Adaptive Joint SCAMP Filter and Relay Weight Optimization Scheme for a wireless Amplify-and-Forward (AF) cooperative relay network operating over frequency-selective fading channels. Conventional AF systems suffer from compounded noise and Inter-Symbol Interference (ISI) due to cascaded multi-tap channel effects. To address these limitations, this work employs a Joint Adaptive Filtering approach that simultaneously optimizes the source pre-coding filter and the relay amplification weight to minimize the end-to-end Mean Squared Error (MSE) and enhance the achievable data rate.The joint optimization problem is solved using the Projected Subgradient Method (PSGM), which provides robustness against non-linear constraints such as sparsity while maintaining low computational complexity. The algorithm is implemented and tested in a MATLAB simulation environment under a time-varying Auto-Regressive (AR(1)) fading model. Key performance metrics such as MSE convergence, filter characteristics, achievable rate, and robustness to parameter variations are analyzed.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch.…