Practical Passive Interference Cancellation Technique For Wireless Networks

With fast increasing demand of the wireless network, the current spectrum used for commercial wireless communication becomes very crowed. So it is critical to find an more efficient way to make the limited spectrum provide larger capacity and throughput. Full-duplex communication technology has caused much attention in the past ten years since it can double the spectrum efficiency theoretically. While the main challenge obstructing it promoting into the market is the self-interference problem in a full duplex system. This dissertation focus on the self-interference cancellation (SIC) theories. The RF impairments occurred in the practical full-duplex system will be discussed. Among them, the phase noise and I/Q imbalance are regarded as the bottleneck of the self-interference cancellation and a detailed analyzing will be included in this dissertation. The general self-interference cancellation methods can be divided into passive self-interference cancellation and active self-interference cancellation where the active cancellation can be further divided into digital cancellation, analog cancellation and hybrid cancellation. This dissertation will review the theories of the passive and active self-interference cancellation. For the analog cancellation, two models (quadratic model and affine model) will be explored to handle the I/Q imbalance and phase noise. Both of these two models are based on the blind tuning algorithm which has two procedures: training and optimizing. This dissertation will introduce the development of the algorithm. It contains the computer simulation results as well as the hardware experimental results to prove the validation of the proposed ideas.

The common thread of the research in this dissertation is to introduce novel interference resilient techniques in multiuser wireless communication systems where the goal of these techniques is to improve system throughput or efficiency and guarantee reliable communication. More specifically, in the first part, we consider the problem of multiplexing wireless data transmission in two-way communication (TWC) channels. Using traditional wireless packet switching methods bidirectional communication tends to double the interference (or time) needed to complete the session. We propose new interference resilient schemes by combining the so called ``two-way relaying'' scheme with a distributed randomized space-time block coding (RSTBC) strategy. RSTBC is a decentralized cooperative technique that ensures diversity gains through the recruitment of multiple uncoordinated relays, with virtually no signaling overhead to enlist relays. In this problem, RSTBC is applied to two-way relaying wireless networks which, when two terminals want to send a message to each other, can potentially improve the network throughput by allowing them to exchange data over two or three time slots via bidirectional relay communications. Specifically, two decode-and-forward (DF) relaying strategies are considered which take up only two time slots. In the first slot the two sources transmit simultaneously. In the former scheme which we refer to as decode and forward both (DFB) RSTBC, only relays which can reliably decode both source blocks via joint maximum likelihood (ML) decoding cooperate, and do so by modulating the bit-level XOR of the decoded data through a single RSTBC. In the latter scheme called decode and forward any (DFA) RSTBC, the relays cooperate in the second slot also when they can decode only one of the two source data. In this case each source data that is decoded is mapped into an independent RSTBC. If the relay decoded reliably both sources, after cancellation of the strong interference, then it sends the two RSTBCs encoding the symbol vectors from each of the sources. A randomized forwarding scheme is also proposed for three-time-slot relaying, which is also a DFA strategy, although without joint decoding or interference cancellation after the first slot. In addition to more judicious transmission and relaying policies, a key ingredient of future wireless network will be enhanced spectrum sensing. This is motivated by the wide adoption of Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems, which offer significant degrees of freedom in encoding data, but at the same time result in a complex spatio-temporal landscape of interference. We combine recent advances in array processing and compressed channel sensing, to solve the problem of estimating the covariance of an asynchronous network of MIMO-OFDM sources. We specifically focus on spectrum sensing (SS) in cognitive radio (CR) systems, since it is of paramount importance to approach the capacity limits for the Secondary Users (SU), while ensuring the undisturbed transmission of Primary Users (PU). In this problem, we formulate a cognitive radio systems spectrum sensing problem in which SU, with multiple receive antennas, senses a channel shared among multiple asynchronous PUs transmitting MIMO-OFDM signals. Lastly, we study online learning and stochastic optimization in cognitive radio system at MAC layer. The typical Compressive Sensing problem models an observer that wants to recover a sparse N dimensional vector from K linear projections of the vector. We combine the ideas of opportunistic spectrum sensing with compressive sensing and introduce the Cognitive Compressive Sensing (CCS) problem which models a cognitive receiver that uses Bayesian beliefs on a dynamically changing sparse vector representing measurements from the signals occupying the sub-channels. The CR objective is to optimally choose the K linear projections with the objective of maximizing a reward from the inference of the sparse vector support. We formulate CCS as a Restless Multi-Armed Bandit problem, generalizing the popular Cognitive Spectrum Sensing model, in which the CR can sense K out of the N sub-channels. We derive the myopic sensing policy that leverages on the beliefs to its inferences. We also propose a greedy counterpart of the myopic sensing policy algorithm with considerably less required computations. While in general the optimum policy remains elusive, we provide sufficient conditions in which in the limit for large K and N the greedy policy is optimum.

The flexibility of wireless signals has rendered it an attractive option for making different daily life applications seamless and towards making connectivity truly ubiquitous. In this dissertation, we leverage relayed wireless signals for enabling communication and sensing. We examine relaying of wireless signals from two dimensions: active and passive. While active relaying refers to relay nodes capable of power amplification of the received signal, passive relaying refers to scenarios of passive relays or reflectors in the path of wireless transmissions. We examine a problem space of uplink traffic and explore the advantages of such active relayed signals for enabling simultaneous uplink transmissions. Specifically, we look at full-duplex wireless communications and full-duplex relays where the relay node is capable of simultaneous transmission and reception in the same frequency band. Traditionally, active relaying has been used primarily for range extension between a transmitter-receiver pair, however, we look at leveraging full-duplex wireless relaying towards the removal of pre-coding requirements for interference cancellation on the clients' ends. Such a design can enable simultaneous transmissions from resource constrained transmitter nodes such as the sensors in an IoT (Internet of Things) paradigm. We evaluate our design using both channel traces from SDRs (Software Defined Radios) as well as network level simulations. We also detail techniques for addressing practical challenges towards the design's practical implementations. We next look at passive relayed wireless signals. Wireless signals transmitted from a transmitting antenna get reflected from objects in the environment where such objects can be considered as passive relays. We analyse these passive relayed signals received at the receiving antenna over water surface to enable the sensing of debris over water surface for monitoring of water pollution. We sense the effect of these floating debris on the waves on the water surface and track the changes caused by the debris to detect the presence of the floating debris. We implement this on SDR platform (WARP v3 node) and demonstrate the detection of low reflecting floating plastic debris which is challenging to detect using wireless signals due it's low reflectivity properties. We include modelling for our system based on ray-tracing for the composite channel between the antennas and the water surface and design search operations for locating debris points. We also include outdoor data collected over outdoor water bodies like outdoor swimming pool and river. Such a wireless based detection system can be a lightweight and privacy preserving solution for monitoring of water-bodies and can assist other technologies for monitoring of health of water-bodies.

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 students in electrical engineering and computer science studying wireless communications will also find this book useful as a secondary textbook.