Optimization of Training and Scheduling in the Non-Coherent SIMO Multiple Access Channel

Channel state information (CSI) is important for achieving large rates in MIMO channels. However, in time-varying MIMO channels, there is a tradeoff between the time/energy spent acquiring channel state information (CSI) and the time/energy remaining for data transmission. This tradeoff is accentuated in the MIMO multiple access channel (MAC), since the number of channel vectors to be estimated increases with the number of users. Furthermore, the problem of acquiring CSI is tightly coupled with the problem of exploiting CSI through multiuser scheduling. This paper considers a block-fading MAC with coherence time T, n uncoordinated users-each with one transmit antenna and the same average power constraint, and a base station with M receive antennas and no a priori CSI. For this scenario, a training-based communication scheme is proposed and the training and multiuser-scheduling aspects of the scheme are jointly optimized. In the high-SNR regime, the sum capacity of the non-coherent SIMO MAC is characterized and used to establish the SNR-scaling-law optimality of the proposed scheme. In the low-SNR regime, the sum-rate of the proposed scheme is found to decay linearly with vanishing SNR when flash signaling is incorporated. Furthermore, this linear decay is shown to be order-optimal through comparison to the low-SNR sum capacity of the non-coherent SIMO MAC. A by product of these SNR-asymptotic analyses is the observation that non-trivial scheduling (i.e., scheduling a strict subset of trained users) is advantageous at low SNR, but not at high SNR. The sum-rate and per-user throughput are also explored in the large-n and large-M regimes. Non-coherent capacity, training, multiple access channel, multiuser scheduling, opportunistic scheduling.

[1]  Emre Telatar,et al.  Capacity of Multi-antenna Gaussian Channels , 1999, Eur. Trans. Telecommun..

[2]  Lizhong Zheng,et al.  Communication on the Grassmann manifold: A geometric approach to the noncoherent multiple-antenna channel , 2002, IEEE Trans. Inf. Theory.

[3]  Babak Hassibi,et al.  How much training is needed in multiple-antenna wireless links? , 2003, IEEE Trans. Inf. Theory.

[4]  Muriel Médard,et al.  Bandwidth scaling for fading multipath channels , 2002, IEEE Trans. Inf. Theory.

[5]  Antonia Maria Tulino,et al.  Multiple-antenna capacity in the low-power regime , 2003, IEEE Trans. Inf. Theory.

[6]  Muriel Médard,et al.  The effect upon channel capacity in wireless communications of perfect and imperfect knowledge of the channel , 2000, IEEE Trans. Inf. Theory.

[7]  Andrea J. Goldsmith,et al.  Capacity limits of MIMO channels , 2003, IEEE J. Sel. Areas Commun..

[8]  Michael L. Honig,et al.  Wideband fading channel capacity with training and limited feedback , 2005 .

[9]  Thomas L. Marzetta,et al.  Multiple-antenna channel hardening and its implications for rate feedback and scheduling , 2004, IEEE Transactions on Information Theory.

[10]  Muriel Médard,et al.  Channel Coherence in the Low-SNR Regime , 2007, IEEE Transactions on Information Theory.

[11]  M. Medard,et al.  Spreading in block-fading channels , 2000, Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154).

[12]  M. J. Gans,et al.  On Limits of Wireless Communications in a Fading Environment when Using Multiple Antennas , 1998, Wirel. Pers. Commun..

[13]  David Tse,et al.  Fundamentals of Wireless Communication , 2005 .

[14]  Gerald B. Folland,et al.  Real Analysis: Modern Techniques and Their Applications , 1984 .

[15]  Babak Hassibi,et al.  Analysis of multiple-antenna wireless links at low SNR , 2004, IEEE Transactions on Information Theory.