Opportunistic Channel Estimation for Implicit 802.11af MU-MIMO

Multi-User MIMO (MU-MIMO) linear channel coding can greatly increase wireless system capacity when Stations (STAs) have fewer antennas than the Access Point (AP), but it comes at the cost of significant Channel State Information (CSI) estimation overhead. Previous work has suggested that 802.11af MU-MIMO systems might benefit from long channel coherence time, extending the useful duration of CSI. In this paper, we propose and analyze an opportunistic channel sounding policy that avoids sounding overhead in wireless channels by gathering implicit CSI opportunistically. This policy not only avoids CSI overhead, but also has the potential to enable efficient interoperability of multi-user APs with legacy single-stream STAs. To investigate the performance of this new policy, we implement a new mobile channel sounding framework on a custom 802.11af Software-Defined Radio (SDR) system designed for UHF-band experimentation and evaluate channel sounding performance in indoor and outdoor environments under various mobility modes. Additional protocol analysis shows that in UHF channels with sufficient channel coherence time, an opportunistic channel sounding policy offers significant protocol optimization while improving the scalability of next-generation MU-MIMO systems.

[1]  Seokjoo Shin,et al.  A MAC protocol to select optimal transmission mode in very high throughput WLAN: MU-MIMO vs. multiple SU-MIMO , 2012, 2012 Third Asian Himalayas International Conference on Internet.

[2]  Thomas L. Marzetta,et al.  Argos: practical many-antenna base stations , 2012, Mobicom '12.

[3]  Edward W. Knightly,et al.  The case for UHF-band MU-MIMO , 2014, MobiCom.

[4]  Edward W. Knightly,et al.  Design and experimental evaluation of multi-user beamforming in wireless LANs , 2010, MobiCom.

[5]  Santosh Pandey,et al.  IEEE 802.11af: a standard for TV white space spectrum sharing , 2013, IEEE Communications Magazine.

[6]  Halim Yanikomeroglu,et al.  Enhancing cell-edge performance: a downlink dynamic interference avoidance scheme with inter-cell coordination , 2010, IEEE Transactions on Wireless Communications.

[7]  Yuanan Liu,et al.  Simplified Semi-Orthogonal User Selection for MU-MIMO Systems with ZFBF , 2012, IEEE Wireless Communications Letters.

[8]  Alexandra Duel-Hallen,et al.  Fading Channel Prediction for Mobile Radio Adaptive Transmission Systems , 2007, Proceedings of the IEEE.

[9]  Sung-Ju Lee,et al.  Mode and user selection for multi-user MIMO WLANs without CSI , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).

[10]  Theodore S. Rappaport,et al.  Measurements and models for radio path loss and penetration loss in and around homes and trees at 5.85 GHz , 1998, IEEE Trans. Commun..

[11]  Monisha Ghosh,et al.  A comparison of implicit and explicit channel feedback methods for MU-MIMO WLAN systems , 2013, 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[12]  Xinyu Zhang,et al.  Adaptive feedback compression for MIMO networks , 2013, MobiCom.

[13]  Florian Kaltenberger,et al.  Towards practical channel reciprocity exploitation: Relative calibration in the presence of frequency offset , 2013, 2013 IEEE Wireless Communications and Networking Conference (WCNC).

[14]  Clayton Shepard,et al.  Control Channel Design for Many-Antenna MU-MIMO , 2015, MobiCom.

[15]  Edward W. Knightly,et al.  MUTE: Sounding inhibition for MU-MIMO WLANs , 2014, 2014 Eleventh Annual IEEE International Conference on Sensing, Communication, and Networking (SECON).

[16]  Andrea J. Goldsmith,et al.  On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming , 2006, IEEE Journal on Selected Areas in Communications.

[17]  Dhanesh Raj,et al.  Performance measurement and analysis of long range Wi-Fi network for over-the-sea communication , 2015, 2015 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt).

[18]  Jaume Barceló,et al.  On the Performance of Packet Aggregation in IEEE 802.11ac MU-MIMO WLANs , 2012, IEEE Communications Letters.