Using MATLAB in Calculus

Using MATLAB in Calculus

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Blind synchronization with single- and multi-sensor arrays Space-time transmit-receive diversity combining systems New physical layer solutions for CDMA and multicarrier systems For every engineering professional involved with signal processing for advanced communications Key advances in signal processing for single-user and multi-user systems. Signal Processing Advances in Communication, Volume II is the second in a two-volume set that introduces important recent advances in signal processing (SP) tools for wireless and mobile communications, and bringing together contributions by leaders in the field worldwide. This two-volume set covers an exceptionally wide range of technologies and methodologies, including noise and interference cancellation, modem design, mobile Internet services, next-generation audio/video broadcasting, cellular telephony, and wireless multimedia networks.
Volume II focuses on single- and multi-user communication systems, presenting an exceptionally wide range of today's best work on topics such as: Blind synchronization with single- and multi-sensor arrays Space-time transmit-receive diversity combining systems Time-varying channel modeling Signal separation with constant modulus constraints Parallel factor analysis tools New methods for canceling multiuser interference and mitigating multipath effects in CDMA and multicarrier systems at the physical layer Key signal processing issues at the network layer This book brings together research previously scattered across multiple journals worldwide, delivering an unprecedented collection of advanced SP techniques for practicing engineers, researchers, managers, and any professional involved with designing or building state-of-the-art single- or multi-user communications systems.
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Product details

  • Paperback | 192 pages
  • 198.1 x 251.5 x 12.7mm | 362.88g
  • Pearson
  • Upper Saddle River, NJ, United States
  • English
  • 013027268X
  • 9780130272683

Table of contents

Preface. 1. Time Varying Fading Channels. Channel Model. Coding Strategies for Transmissions over LTV Channels. Channel Estimation and Prediction. Conclusion. Appendices. Bibliography. 2. Space-Time Diversity. Introduction. The Set-Up. General Framework for Detection. Space-Only Processing. Space-Time Processing. Bit Error Rate. Data Rate. Discussion. Conclusions. Bibliography. 3. Algebraic Constant Modulus Algorithms. Introduction. Preliminaries. Derivation ofthe ACMA. Analysis ofthe Noise-free Case. ACMA in Noise. Asymptotic Behavior. Weighted ACMA. Binary Source Separation. Simulations. Joint Diagonalization. Concluding Remarks. Bibliography. 4. Parafac Techniques For Signal Separation. Introduction. Theory. Algorithms for fitting the PARAFAC Model. Determining Three-Way Array Rank. Applications - Part I: Data Modeling. Applications - Part II: Examples. PARAFAC Extensions: PARAFAC2. Conclusions. Bibliography. 5. Multipath Mitigation In Cdma Systems. Introduction. Signal Model. Receiver Design. Minimum Variance Receivers. Multipath Mitigation in Long Code Systems. Conclusions. Bibliography. 6. Block Spreading For Multipath Resilient Generalized Multi-Carrier Cdma. Block Spreading Model. GMC-CDMA for MUI/ISI-free Multirate Transmissions. Performance and Comparisons. Conclusions and Discussion. Appendix 6:.A Dual Vandermonde-Lagrange Transceivers. Appendix 6:.B Modulo-Interpretation of GMC-CDMA. Bibliography. 7. Multistage Interference Cancellation Algorithms For Ds/Cdma Signals. Introduction. Multiuser Signal Model. Overview of CDMA Receivers. Successive Interference Canceler (SIC). Exact BER Analysis. Approximate BER Analysis. Adaptive SIC (ASIC). Parallel Interference Canceler (PIC). BER Analysis for the PIC. State-Space Analysis. Conclusion. Bibliography. 8. Signal Processing Based Collision Resolution. Packet Collision in Slotted Aloha Ad Hoc Networks. Packet Collision Model. The Training-based Zero Forcing Receiver. The Semi-blind Least Squares Smoothing Receiver. Blind Receivers. Resolvability Analysis. Network Performance Analysis. Numerical Examples. Concluding Remarks. Appendix.: Bibliography. 9. Non-Data-Aided Digital Synchronization. Introduction. Signal Model. Classical Unconditional Maximum Likelihood (UML) Approach. Conditional Maximum Likelihood (CML)Approach. Minimum Conditioned Variance Compressed Likelihood Function (MCV-CML) Approach. Bounds and Performance Evaluation. Conclusions. Bibliography. 10. Exploiting Antenna Arrays For Synchronization. Introduction. Data Model. Maximum Likelihood Estimator. An Asymptotically Equivalent Estimator. Heuristic Derivations. Calculating the Estimates with IQML and ESPRIT. Simulation Results. Conclusions. Appendix 1:0.A. Bibliography. Index.
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