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.

VL - 16
IS - 6
ER -
TY - CONF
T1 - Frequency selective multiuser hybrid precoding for mmWave systems with imperfect channel knowledge
T2 - Asilomar Conf. on Signals, Systems and Computers
Y1 - 2016
A1 - Jose P. Gonzalez-Coma
A1 - Nuria González-Prelcic
A1 - Luis Castedo
A1 - Robert W. Heath Jr.
KW - compass
KW - mmWave
JF - Asilomar Conf. on Signals, Systems and Computers
ER -
TY - CONF
T1 - FER prediction with variable codeword length
T2 - ICASSP2014 - Signal Processing for Communications and Networking (ICASSP2014 - SPCOM)
Y1 - 2014
A1 - Alberto Rico-Alvariño
A1 - Robert W. Heath Jr.
A1 - Carlos Mosquera
KW - adaptive signal processing
KW - compass
KW - dynacs
KW - Effective SNR
KW - FER prediction
KW - PHY abstraction
AB - Frame error rate (FER) prediction in wireless communication systems is an important tool with applications to system level simulations and link adaptation, among others. Although in realistic communication scenarios it is expected to have codewords of different lengths, previous work on FER prediction marginally treated the dependency of the FER on the codeword length. In this paper, we present a method to estimate the FER using codewords of different length. We derive a low complexity FER estimator for frames of different length transmitted over a binary symmetric channel of unknown error probability. We extend this technique to coded systems by the use of effective SNR FER predictors. The proposed estimation scheme is shown to outperform other simpler estimation methods.

JF - ICASSP2014 - Signal Processing for Communications and Networking (ICASSP2014 - SPCOM) CY - Florence, Italy ER -