Robust Rate-Adaptive Wireless Communication Using ACK/NAK-Feedback

• Published in: IEEE transactions on signal processing Vol. 60; no. 4; pp. 1752 - 1765
• Main Authors: Koksal, C. E., Schniter, P.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.04.2012; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive modulation; Applied sciences; Asymptotic properties; automatic repeat request; Channel estimation; Channels; cross-layer strategies; Detection, estimation, filtering, equalization, prediction; Error analysis; Errors; Exact sciences and technology; Feedback; Gaussian; Information, signal and communications theory; Modulation, demodulation; Optimization; Quadrature amplitude modulation; rate adaptation; Receivers; Signal and communications theory; Signal to noise ratio; Signal, noise; Studies; Telecommunications and information theory; Transmitters; Upper bound; Upper bounds; Wireless communication; Parameter estimation; Quadrature amplitude modulation; Wireless telecommunication; Error rate; Feedback regulation; Adaptive estimation; Packet error rate; Learning; Channel estimation; Cross-layer approach; Traffic control; Adaptive modulation; Prior distribution; cross-layer strategies; Flow rate regulation; Teletraffic; Signalling; Upper bound; Traffic management; rate adaptation; Telecommunication channels; Signal processing; Transmission rate; Automatic repeat request; Transmission error; Recursive estimation
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/TSP.2011.2179541

To combat the detrimental effects of the variability in wireless channels, we consider cross-layer rate adaptation based on limited feedback. In particular, based on limited feedback in the form of link-layer acknowledgements (ACK) and negative acknowledgements (NAK), we maximize the physical-layer transmission rate subject to an upper bound on the expected packet error rate. We take a robust approach in that we do not assume any particular prior distribution on the channel state. We first analyze the fundamental limitations of such systems and derive an upper bound on the achievable rate for signaling schemes based on uncoded QAM and random Gaussian ensembles. We show that, for channel estimation based on binary ACK/NAK feedback, it may be preferable to use a separate training sequence at high error rates, rather than to exploit low-error-rate data packets themselves. We also develop an adaptive recursive estimator, which is provably asymptotically optimal and asymptotically efficient.