We propose a novel mode of operation for Amplify-and-

Forward relays in which the spectra of the relay input and

output signals partially overlap. This partial-duplex relaying mode

encompasses half- and full-duplex as particular cases. By viewing

the partial-duplex relay as a bandwidth-preserving Linear

Periodically Time-Varying system, a spectral efficiency analysis

under self-interference is developed. In contrast with previous

works, self-interference is regarded as a useful informationbearing

component rather than simply assimilated to noise. This

approach reveals that previous results regarding the impact of

self-interference on (full-duplex) relay performance are overly

pessimistic. Based on a frequency-domain interpretation of the

effect of self-interference, a number of suboptimal decoding

architectures at the destination node are also discussed. It is found

that the partial-duplex relaying mode may provide an attractive

tradeoff between spectral efficiency and receiver complexity.

%B IEEE Transactions on Wireless Communications
%V 18
%P 2271-2285
%8 04/2019
%G eng
%N 4
%R 10.1109/TWC.2019.2902390
%0 Journal Article
%J IEEE Transactions on Wireless Communications
%D 2017
%T FER Estimation in a Memoryless BSC with Variable Frame Length and Unreliable ACK/NAK Feedback
%A Alberto Rico-Alvariño
%A R. López-Valcarce
%A Carlos Mosquera
%A Robert W. Heath Jr.
%K adaptive signal processing
%K compass
%K Cramér-Rao bound (CRB)
%K frame error rate
%K myrada
%K winter
%X We consider the problem of estimating the frame error rate (FER) of a given memoryless binary symmetric channel by observing the success or failure of transmitted packets. Whereas FER estimation is relatively straightforward if all observations correspond to packets with equal length, the problem becomes considerably more complex when this is not the case. We develop FER estimators when

transmissions of different lengths are observed, together with the Cramer-Rao Lower Bound (CRLB). Although the main focus is on Maximum Likelihood (ML) estimation, we also obtain low complexity schemes performing close to optimal in some scenarios. In a second stage, we consider the case in which FER estimation is performed at a node different from the receiver, and incorporate the impairment of unreliable observations by considering noisy ACK/NAK feedback links. The impact of unreliable feedback is analyzed by means of the corresponding CRLB. In this setting, the ML estimator is obtained by applying the Expectation-Maximization algorithm to jointly estimate the error probabilities of the data and feedback links. Simulation results illustrate the benefits of the proposed estimators.

%B IEEE Transactions on Wireless Communications
%V 16
%P 3661 - 3673
%8 06/2017
%G eng
%N 6
%R 10.1109/TWC.2017.2686845
%0 Conference Paper
%B IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
%D 2017
%T Time-domain channel estimation for wideband millimeter wave systems with hybrid architecture
%A Kiran Venugopal
%A Ahmed Alkhateeb
%A Robert W. Heath Jr.
%A Nuria González-Prelcic
%K compass
%K mmWave
%K myrada
%X Millimeter wave (mm Wave) systems will likely employ large antennas at both the transmitter and receiver for directional beamforming. Hybrid analog/digital MIMO architectures have been proposed previously for leveraging both array gain and multiplexing gain, while reducing the power consumption in analog-to-digital converters. Channel knowledge is needed to design the hybrid precoders/combiners, which is difficult to obtain due to the large antenna arrays and the frequency selective nature of the channel. In this paper, we propose a sparse recovery based time-domain channel estimation technique for hybrid architecture based frequency selective mmWave systems. The proposed compressed sensing channel estimation algorithm is shown to provide good estimation error performance, while requiring small training overhead. The simulation results show that using multiple RF chains at the receiver and the transmitter further reduces the training overhead.

%B IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) %P 6193-6197 %8 03/2017 %G eng