Full-Duplex Wireless Communications Systems

This book introduces the development of self-interference (SI)-cancellation techniques for full-duplex wireless communication systems. The authors rely on estimation theory and signal processing to develop SI-cancellation algorithms by generating an estimate of the received SI and subtracting it from the received signal.

The authors also cover two new SI-cancellation methods using the new concept of active signal injection (ASI) for full-duplex MIMO-OFDM systems. The ASI approach adds an appropriate cancelling signal to each transmitted signal such that the combined signals from transmit antennas attenuate the SI at the receive antennas. The authors illustrate that the SI-pre-cancelling signal does not affect the data-bearing signal. This book is for researchers and professionals working in wireless communications and engineers willing to understand the challenges of deploying full-duplex and practical solutions to implement a full-duplex system. Advanced-level studentsin electrical engineering and computer science studying wireless communications will also find this book useful as a secondary textbook.

Provides a comprehensive investigation of technical challenges in self-interference cancellation for full-duplex systems Includes a wide range of self-interference cancellation methods Presents a complete discussion about self-interference cancellation techniques that covers passive RF cancellation, active RF cancellation and baseband cancellation Develops a new baseband cancellation techniques that consider the statistics of the unknown intended signal Proposes an original self-interference cancellation, based on the concept of signal injection that avoids the drawbacks of existent methods Includes supplementary material: sn.pub/extras Includes supplementary material: sn.pub/extras

Inhalt

1. Introduction.- 2 Self-Interference Cancellation in Full-Duplex Systems.- 3 Limiting Factors in Self-Interference Cancellation.- 4 Self-Interference Channel Estimation and Cancellation Using Compressed-Sensing and Subspace.- 5 Widely-Linear Subspace-Based Self-Interference Cancellation.- 6 Maximum Likelihood-Based Self-Interference Cancellation.- 7 Active Signal Injection for Self-Interference Cancellation.- 8 Conclusions and Future Work.- References.<p