3,406 research outputs found
Event-Driven Optimal Feedback Control for Multi-Antenna Beamforming
Transmit beamforming is a simple multi-antenna technique for increasing
throughput and the transmission range of a wireless communication system. The
required feedback of channel state information (CSI) can potentially result in
excessive overhead especially for high mobility or many antennas. This work
concerns efficient feedback for transmit beamforming and establishes a new
approach of controlling feedback for maximizing net throughput, defined as
throughput minus average feedback cost. The feedback controller using a
stationary policy turns CSI feedback on/off according to the system state that
comprises the channel state and transmit beamformer. Assuming channel isotropy
and Markovity, the controller's state reduces to two scalars. This allows the
optimal control policy to be efficiently computed using dynamic programming.
Consider the perfect feedback channel free of error, where each feedback
instant pays a fixed price. The corresponding optimal feedback control policy
is proved to be of the threshold type. This result holds regardless of whether
the controller's state space is discretized or continuous. Under the
threshold-type policy, feedback is performed whenever a state variable
indicating the accuracy of transmit CSI is below a threshold, which varies with
channel power. The practical finite-rate feedback channel is also considered.
The optimal policy for quantized feedback is proved to be also of the threshold
type. The effect of CSI quantization is shown to be equivalent to an increment
on the feedback price. Moreover, the increment is upper bounded by the expected
logarithm of one minus the quantization error. Finally, simulation shows that
feedback control increases net throughput of the conventional periodic feedback
by up to 0.5 bit/s/Hz without requiring additional bandwidth or antennas.Comment: 29 pages; submitted for publicatio
Very Low-Rate Variable-Length Channel Quantization for Minimum Outage Probability
We identify a practical vector quantizer design problem where any
fixed-length quantizer (FLQ) yields non-zero distortion at any finite rate,
while there is a variable-length quantizer (VLQ) that can achieve zero
distortion with arbitrarily low rate. The problem arises in a
multiple-antenna fading channel where we would like to minimize the channel
outage probability by employing beamforming via quantized channel state
information at the transmitter (CSIT). It is well-known that in such a
scenario, finite-rate FLQs cannot achieve the full-CSIT (zero distortion)
outage performance. We construct VLQs that can achieve the full-CSIT
performance with finite rate. In particular, with denoting the power
constraint of the transmitter, we show that the necessary and sufficient VLQ
rate that guarantees the full-CSIT performance is . We also
discuss several extensions (e.g. to precoding) of this result
Bit Allocation Law for Multi-Antenna Channel Feedback Quantization: Single-User Case
This paper studies the design and optimization of a limited feedback
single-user system with multiple-antenna transmitter and single-antenna
receiver. The design problem is cast in form of the minimizing the average
transmission power at the base station subject to the user's outage probability
constraint. The optimization is over the user's channel quantization codebook
and the transmission power control function at the base station. Our approach
is based on fixing the outage scenarios in advance and transforming the design
problem into a robust system design problem. We start by showing that uniformly
quantizing the channel magnitude in dB scale is asymptotically optimal,
regardless of the magnitude distribution function. We derive the optimal
uniform (in dB) channel magnitude codebook and combine it with a spatially
uniform channel direction codebook to arrive at a product channel quantization
codebook. We then optimize such a product structure in the asymptotic regime of
, where is the total number of quantization feedback
bits. The paper shows that for channels in the real space, the asymptotically
optimal number of direction quantization bits should be times
the number of magnitude quantization bits, where is the number of base
station antennas. We also show that the performance of the designed system
approaches the performance of the perfect channel state information system as
. For complex channels, the number of magnitude and
direction quantization bits are related by a factor of and the system
performance scales as as .Comment: Submitted to IEEE Transactions on Signal Processing, March 201
On Low-Resolution ADCs in Practical 5G Millimeter-Wave Massive MIMO Systems
Nowadays, millimeter-wave (mmWave) massive multiple-input multiple-output
(MIMO) systems is a favorable candidate for the fifth generation (5G) cellular
systems. However, a key challenge is the high power consumption imposed by its
numerous radio frequency (RF) chains, which may be mitigated by opting for
low-resolution analog-to-digital converters (ADCs), whilst tolerating a
moderate performance loss. In this article, we discuss several important issues
based on the most recent research on mmWave massive MIMO systems relying on
low-resolution ADCs. We discuss the key transceiver design challenges including
channel estimation, signal detector, channel information feedback and transmit
precoding. Furthermore, we introduce a mixed-ADC architecture as an alternative
technique of improving the overall system performance. Finally, the associated
challenges and potential implementations of the practical 5G mmWave massive
MIMO system {with ADC quantizers} are discussed.Comment: to appear in IEEE Communications Magazin
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