Fundamentals of Efficient Spectrum Access and Co-existence with Receiver Nonlinearity

RF front-ends are nonlinear systems that have nonlinear frequency response and, hence, can impair receiver performance by harmful adjacent channel interference in non-intuitive ways. Next generation wireless networks will see unprecedented diversity across receiver and radio technologies accessing the same band of spectrum in spatio-temporal proximity. Ensuring adjacent channel co-existence is of prime importance for successful deployment and operations of next generation wireless networks. Vulnerabilities of receiver front-end can have a severe detrimental effect on network performance and spectrum co-existence. This dissertation addresses the technological challenges in understanding and accounting for receiver sensitivities in the design of next generation wireless networks. The dissertation has four major contributions.

In the first contribution, we seek to understand how receiver nonlinearity impacts performance. We propose a computationally efficient framework to evaluate the adjacent channel interference in a given radio/spectrum environment. We develop novel tractable representation of receiver front-end nonlinearity to specify the adjacent channel signals that contribute to the interference at the desired channel and the total adjacent channel interference power at a given desired channel.

In the second contribution, we seek to understand how the impact of receiver nonlinearity performance can be quantified. We quantify receiver performance in the presence of adjacent channel interference using information theoretic metrics. We evaluate the limits on achievable rate accounting for RF front-end nonlinearity and provide a framework to compare disparate receivers by forming generalized metrics.

In the third contribution, we seek to understand how the impact of receiver nonlinearity can be managed at the network level. We develop novel and comprehensive wireless network management frameworks that account for the RF nonlinearity, impairments, and diversity of heterogeneous wireless devices. We further develop computationally efficient algorithms to optimize the proposed framework and examine network level performance. We demonstrate through extensive network simulations that the proposed receiver-centric frameworks provide substantially high spectrum efficiency gains over receiver-agnostic spectrum access in dense and diverse next generation wireless networks.

In the fourth contribution, we seek to understand how scalable interference networks are with receiver nonlinearity. We propose practical achievable schemes for interference avoidance and assess the scalability of the next generation wireless networks with interference due to receiver nonlinearity. Further, we develop an algorithmic scheme to evaluate the upper bound on scalability of nonlinear interference networks. This provides valuable insights on scalability and schemes for nonlinear adjacent channel interference avoidance in next generation shared spectrum networks.