Performance of Quantized Random Beamforming in Delay-Tolerant Machine-Type Communication

Machine-to-machine (M2M) communication represents a new paradigm for mobile cellular networks, where a massive number of low-cost devices request the transfer of small amounts of data without human intervention. One option to tackle this problem is obtained by combining random beamforming (RBF) with opportunistic scheduling. RBF can be used to induce larger channel fluctuations, and opportunistic scheduling can be used to select M2M devices when their overall channel quality is good. Traditional RBF does not fulfill M2M requirements, because overall channel quality needs to be tracked continuously. In order to tackle this limitation, a novel codebook-based RBF architecture that identifies in advance the time instants in which overall channel quality should be reported, within a coherence time window, is proposed. This opportunistic feedback mechanism reduces signaling overhead and enables energy saving at M2M devices. A simplified methodology is presented to evaluate the system mean data rate, using for this purpose closed form formulas derived from SNR distribution approximations. Results reveal that the performance loss that is experienced for introducing the proposed modifications to traditional RBF scheme is negligible. The concepts analyzed in this paper provide useful insights, and show that codebook-based RBF with simplified opportunistic scheduling algorithms is an excellent combination to provide wide-area M2M services with low-cost devices and limited signaling overhead.

[1]  Yik-Chung Wu,et al.  Non-Orthogonal Opportunistic Beamforming: Performance Analysis and Implementation , 2012, IEEE Transactions on Wireless Communications.

[2]  Ove Edfors,et al.  The effect of feedback quantization on the throughput of a multiuser diversity scheme , 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).

[3]  Young-Chai Ko,et al.  Exact Sum-Rate Analysis of MIMO Broadcast Channels with Random Unitary Beamforming , 2011, IEEE Trans. Commun..

[4]  M. Abramowitz,et al.  Handbook of Mathematical Functions With Formulas, Graphs and Mathematical Tables (National Bureau of Standards Applied Mathematics Series No. 55) , 1965 .

[5]  Minghua Xia,et al.  Opportunistic cophasing transmission in MISO systems , 2009, IEEE Transactions on Communications.

[6]  Tharaka Samarasinghe,et al.  Optimal Selective Feedback Policies for Opportunistic Beamforming , 2011, IEEE Transactions on Information Theory.

[7]  S. Parkvall,et al.  LTE release 12 and beyond [Accepted From Open Call] , 2013, IEEE Communications Magazine.

[8]  David James Love,et al.  On the performance of random vector quantization limited feedback beamforming in a MISO system , 2007, IEEE Transactions on Wireless Communications.

[9]  Yichao Huang,et al.  Closed Form Sum Rate of Random Beamforming , 2012, IEEE Communications Letters.

[10]  Risto Wichman,et al.  On Throughput-Fairness Tradeoff in Virtual MIMO Systems with Limited Feedback , 2009, EURASIP J. Wirel. Commun. Netw..

[11]  Aria Nosratinia,et al.  Exploiting multiuser diversity with only 1-bit feedback , 2005, IEEE Wireless Communications and Networking Conference, 2005.

[12]  Naresh Sharma,et al.  A study of opportunism for multiple-antenna systems , 2005, IEEE Transactions on Information Theory.

[13]  Roberto Garrappa,et al.  Some Formulas for Sums of Binomial Coefficients and Gamma Functions , 2007 .

[14]  Özgür Özdemir,et al.  Optimum feedback quantization in an opportunistic beamforming scheme , 2010, IEEE Transactions on Wireless Communications.

[15]  Dusit Niyato,et al.  Random access for machine-to-machine communication in LTE-advanced networks: issues and approaches , 2013, IEEE Communications Magazine.

[16]  Özgür Özdemir,et al.  SPC05-6: Performance of Opportunistic Beamforming with Quantized Feedback , 2006, IEEE Globecom 2006.

[17]  Chungyong Lee,et al.  An Opportunistic Beamforming Technique Using a Quantized Codebook , 2007, 2007 IEEE 65th Vehicular Technology Conference - VTC2007-Spring.

[18]  David Tse,et al.  Opportunistic beamforming using dumb antennas , 2002, IEEE Trans. Inf. Theory.

[19]  Tarik Taleb,et al.  Machine type communications in 3GPP networks: potential, challenges, and solutions , 2012, IEEE Communications Magazine.

[20]  B. D. Hughes Random Walks and Random Environments, Volume 1: Random Walks.@@@Random Walks and Random Environments, Volume 2: Random Environments. , 1998 .

[21]  Babak Hassibi,et al.  On the capacity of MIMO broadcast channels with partial side information , 2005, IEEE Transactions on Information Theory.

[22]  Hong-Chuan Yang,et al.  Performance analysis of low-complexity dual-cell random beamforming transmission with user scheduling , 2011, EURASIP J. Wirel. Commun. Netw..

[23]  Alexis Alfredo Dowhuszko,et al.  On the Analysis and Design of Practical Quantization for Opportunistic Beamforming , 2008, 2008 IEEE International Conference on Communications.

[24]  Rayleigh The Problem of the Random Walk , 1905, Nature.