3,706 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
Optimal Beamforming for Gaussian MIMO Wiretap Channels with Two Transmit Antennas
A Gaussian multiple-input multiple-output wiretap channel in which the
eavesdropper and legitimate receiver are equipped with arbitrary numbers of
antennas and the transmitter has two antennas is studied in this paper. Under
an average power constraint, the optimal input covariance to obtain the secrecy
capacity of this channel is unknown, in general. In this paper, the input
covariance matrix required to achieve the capacity is determined. It is shown
that the secrecy capacity of this channel can be achieved by linear precoding.
The optimal precoding and power allocation schemes that maximize the achievable
secrecy rate, and thus achieve the capacity, are developed subsequently. The
secrecy capacity is then compared with the achievable secrecy rate of
generalized singular value decomposition (GSVD)-based precoding, which is the
best previously proposed technique for this problem. Numerical results
demonstrate that substantial gain can be obtained in secrecy rate between the
proposed and GSVD-based precodings.Comment: Accepted for publication in IEEE Transactions on Wireless
Communication
On the MISO Channel with Feedback: Can Infinitely Massive Antennas Achieve Infinite Capacity?
We consider communication over a multiple-input single-output (MISO) block
fading channel in the presence of an independent noiseless feedback link. We
assume that the transmitter and receiver have no prior knowledge of the channel
state realizations, but the transmitter and receiver can acquire the channel
state information (CSIT/CSIR) via downlink training and feedback. For this
channel, we show that increasing the number of transmit antennas to infinity
will not achieve an infinite capacity, for a finite channel coherence length
and a finite input constraint on the second or fourth moment. This insight
follows from our new capacity bounds that hold for any linear and nonlinear
coding strategies, and any channel training schemes. In addition to the channel
capacity bounds, we also provide a characterization on the beamforming gain
that is also known as array gain or power gain, at the regime with a large
number of antennas.Comment: This work has been submitted to the IEEE Transactions on Information
Theory. It was presented in part at ISIT201
MISO Capacity with Per-Antenna Power Constraint
We establish in closed-form the capacity and the optimal signaling scheme for
a MISO channel with per-antenna power constraint. Two cases of channel state
information are considered: constant channel known at both the transmitter and
receiver, and Rayleigh fading channel known only at the receiver. For the first
case, the optimal signaling scheme is beamforming with the phases of the beam
weights matched to the phases of the channel coefficients, but the amplitudes
independent of the channel coefficients and dependent only on the constrained
powers. For the second case, the optimal scheme is to send independent signals
from the antennas with the constrained powers. In both cases, the capacity with
per-antenna power constraint is usually less than that with sum power
constraint.Comment: 7 pages double-column, 3 figure
Delay Performance of MISO Wireless Communications
Ultra-reliable, low latency communications (URLLC) are currently attracting
significant attention due to the emergence of mission-critical applications and
device-centric communication. URLLC will entail a fundamental paradigm shift
from throughput-oriented system design towards holistic designs for guaranteed
and reliable end-to-end latency. A deep understanding of the delay performance
of wireless networks is essential for efficient URLLC systems. In this paper,
we investigate the network layer performance of multiple-input, single-output
(MISO) systems under statistical delay constraints. We provide closed-form
expressions for MISO diversity-oriented service process and derive
probabilistic delay bounds using tools from stochastic network calculus. In
particular, we analyze transmit beamforming with perfect and imperfect channel
knowledge and compare it with orthogonal space-time codes and antenna
selection. The effect of transmit power, number of antennas, and finite
blocklength channel coding on the delay distribution is also investigated. Our
higher layer performance results reveal key insights of MISO channels and
provide useful guidelines for the design of ultra-reliable communication
systems that can guarantee the stringent URLLC latency requirements.Comment: This work has been submitted to the IEEE for possible publication.
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