Optimal Signaling of MISO Full-Duplex Two-Way Wireless Channel

We model the self-interference in a multiple input single output (MISO) full-duplex two-way channel and evaluate the achievable rate region. We formulate the boundary of the achievable rate region termed as the Pareto boundary by a family of coupled, non-convex optimization problems. Our main contribution is decoupling and reformulating the original non-convex optimization problems to a family of convex semidefinite programming problems. For a MISO full-duplex two-way channel, we prove that beamforming is an optimal transmission strategy which can achieve any point on the Pareto boundary. Furthermore, we present a closed-form expression for the optimal beamforming weights. In our numerical examples we quantify gains in the achievable rates of the proposed beamforming over the zero-forcing beamforming.Comment: To appear in IEEE ICC 2015, London, U

An Analog Baseband Approach for Designing Full-Duplex Radios

Recent wireless testbed implementations have proven that full-duplex communication is in fact possible and can outperform half-duplex systems. Many of these implementations modify existing half-duplex systems to operate in full-duplex. To realize the full potential of full-duplex, radios need to be designed with self-interference in mind. In our work, we use an experimental setup with a patch antenna prototype to characterize the self-interference channel between two radios. In doing so, we form an analytical model to design analog baseband cancellation techniques. We show that our cancellation scheme can provide up to 10 dB improved signal strength, 2.5 bps/Hz increase in rate, and a 10,000 improvement in BER as compared to the RF only cancellation provided by the patch antenna.Comment: 5 pages, 8 figures, to appear in 2013 Asilomar Conference proceeding

Cooperative Compute-and-Forward

We examine the benefits of user cooperation under compute-and-forward. Much like in network coding, receivers in a compute-and-forward network recover finite-field linear combinations of transmitters' messages. Recovery is enabled by linear codes: transmitters map messages to a linear codebook, and receivers attempt to decode the incoming superposition of signals to an integer combination of codewords. However, the achievable computation rates are low if channel gains do not correspond to a suitable linear combination. In response to this challenge, we propose a cooperative approach to compute-and-forward. We devise a lattice-coding approach to block Markov encoding with which we construct a decode-and-forward style computation strategy. Transmitters broadcast lattice codewords, decode each other's messages, and then cooperatively transmit resolution information to aid receivers in decoding the integer combinations. Using our strategy, we show that cooperation offers a significant improvement both in the achievable computation rate and in the diversity-multiplexing tradeoff.Comment: submitted to IEEE Transactions on Information Theor

Fast Multi-user Detector for a Time-varying CDMA System

This paper investigates methods to reduce the amount of computation needed to detect information bits using a linear detector for a CDMA system. We show windowing technique coupled with pipelining can reduce the amount of computation without significantly sacrificing the performance of linear feedback detector. We also describe efficient techniques to adapt to a dynamic system where the system parameters vary due to the change in delays associated with individual users.Nokia CorporationNational Science FoundationTexas Advanced Technology Progra