Fundamentals of wireless communication
Fundamentals of wireless communication
WARP: a flexible platform for clean-slate wireless medium access protocol design
ACM SIGMOBILE Mobile Computing and Communications Review
Interference alignment and cancellation
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
Limited feedback beamforming over temporally-correlated channels
IEEE Transactions on Signal Processing
Predictable 802.11 packet delivery from wireless channel measurements
Proceedings of the ACM SIGCOMM 2010 conference
What is the value of limited feedback for MIMO channels?
IEEE Communications Magazine
An overview of limited feedback in wireless communication systems
IEEE Journal on Selected Areas in Communications
JMB: scaling wireless capacity with user demands
Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication
Achieving high data rates in a distributed MIMO system
Proceedings of the 18th annual international conference on Mobile computing and networking
Argos: practical many-antenna base stations
Proceedings of the 18th annual international conference on Mobile computing and networking
Simplifying the configuration of 802.11 wireless networks with effective snr
Simplifying the configuration of 802.11 wireless networks with effective snr
NEMOx: scalable network MIMO for wireless networks
Proceedings of the 19th annual international conference on Mobile computing & networking
RobinHood: sharing the happiness in a wireless jungle
Proceedings of the 15th Workshop on Mobile Computing Systems and Applications
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MIMO beamforming technology can scale wireless data rate proportionally with the number of antennas. However, the overhead induced by receivers' CSI (channel state information) feedback scales at a higher rate. In this paper, we address this fundamental tradeoff with Adaptive Feedback Compression (AFC). AFC quantizes or compresses CSI from 3 dimensions --- time, frequency and numerical values, and adapts the intensity of compression according to channel profile. This simple principle faces many practical challenges, e.g., a huge search space for adaption, estimation or prediction of the impact of compression on network throughput, and the coupling of different users in multi-user MIMO networks. AFC meets these challenges using a novel cross-layer adaptation metric, a metric extracted from 802.11 packet preambles, and uses it to guide the selection of compression intensity, so as to balance the tradeoff between overhead reduction and capacity loss (due to compression). We have implemented AFC on a software radio testbed. Our experiments show that AFC can outperform alternative approaches in a variety of radio environments.