1,301 research outputs found
Optimization of Training and Feedback Overhead for Beamforming over Block Fading Channels
We examine the capacity of beamforming over a single-user, multi-antenna link
taking into account the overhead due to channel estimation and limited feedback
of channel state information. Multi-input single-output (MISO) and multi-input
multi-output (MIMO) channels are considered subject to block Rayleigh fading.
Each coherence block contains symbols, and is spanned by training
symbols, feedback bits, and the data symbols. The training symbols are used
to obtain a Minimum Mean Squared Error estimate of the channel matrix. Given
this estimate, the receiver selects a transmit beamforming vector from a
codebook containing {\em i.i.d.} random vectors, and sends the
corresponding bits back to the transmitter. We derive bounds on the
beamforming capacity for MISO and MIMO channels and characterize the optimal
(rate-maximizing) training and feedback overhead ( and ) as and the
number of transmit antennas both become large. The optimal is
limited by the coherence time, and increases as . For the MISO
channel the optimal and (fractional overhead due to training and
feedback) are asymptotically the same, and tend to zero at the rate . For the MIMO channel the optimal feedback overhead tends to zero
faster (as ).Comment: accepted for IEEE Trans. Info. Theory, 201
Optimized Training Design for Wireless Energy Transfer
Radio-frequency (RF) enabled wireless energy transfer (WET), as a promising
solution to provide cost-effective and reliable power supplies for
energy-constrained wireless networks, has drawn growing interests recently. To
overcome the significant propagation loss over distance, employing
multi-antennas at the energy transmitter (ET) to more efficiently direct
wireless energy to desired energy receivers (ERs), termed \emph{energy
beamforming}, is an essential technique for enabling WET. However, the
achievable gain of energy beamforming crucially depends on the available
channel state information (CSI) at the ET, which needs to be acquired
practically. In this paper, we study the design of an efficient channel
acquisition method for a point-to-point multiple-input multiple-output (MIMO)
WET system by exploiting the channel reciprocity, i.e., the ET estimates the
CSI via dedicated reverse-link training from the ER. Considering the limited
energy availability at the ER, the training strategy should be carefully
designed so that the channel can be estimated with sufficient accuracy, and yet
without consuming excessive energy at the ER. To this end, we propose to
maximize the \emph{net} harvested energy at the ER, which is the average
harvested energy offset by that used for channel training. An optimization
problem is formulated for the training design over MIMO Rician fading channels,
including the subset of ER antennas to be trained, as well as the training time
and power allocated. Closed-form solutions are obtained for some special
scenarios, based on which useful insights are drawn on when training should be
employed to improve the net transferred energy in MIMO WET systems.Comment: 30 pages, 9 figures, to appear in IEEE Trans. on Communication
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