1,223 research outputs found
Beamforming in MISO Systems: Empirical Results and EVM-based Analysis
We present an analytical, simulation, and experimental-based study of
beamforming Multiple Input Single Output (MISO) systems. We analyze the
performance of beamforming MISO systems taking into account implementation
complexity and effects of imperfect channel estimate, delayed feedback, real
Radio Frequency (RF) hardware, and imperfect timing synchronization. Our
results show that efficient implementation of codebook-based beamforming MISO
systems with good performance is feasible in the presence of channel and
implementation-induced imperfections. As part of our study we develop a
framework for Average Error Vector Magnitude Squared (AEVMS)-based analysis of
beamforming MISO systems which facilitates comparison of analytical,
simulation, and experimental results on the same scale. In addition, AEVMS
allows fair comparison of experimental results obtained from different wireless
testbeds. We derive novel expressions for the AEVMS of beamforming MISO systems
and show how the AEVMS relates to important system characteristics like the
diversity gain, coding gain, and error floor.Comment: Submitted to IEEE Transactions on Wireless Communications, November
200
Outage Probability of Multiple-Input Single-Output (MISO) Systems with Delayed Feedback
We investigate the effect of feedback delay on the outage probability of
multiple-input single-output (MISO) fading channels. Channel state information
at the transmitter (CSIT) is a delayed version of the channel state information
available at the receiver (CSIR). We consider two cases of CSIR: (a) perfect
CSIR and (b) CSI estimated at the receiver using training symbols. With perfect
CSIR, under a short-term power constraint, we determine: (a) the outage
probability for beamforming with imperfect CSIT (BF-IC) analytically, and (b)
the optimal spatial power allocation (OSPA) scheme that minimizes outage
numerically. Results show that, for delayed CSIT, BF-IC is close to optimal for
low SNR and uniform spatial power allocation (USPA) is close to optimal at high
SNR. Similarly, under a long-term power constraint, we show that BF-IC is close
to optimal for low SNR and USPA is close to optimal at high SNR. With imperfect
CSIR, we obtain an upper bound on the outage probability with USPA and BF-IC.
Results show that the loss in performance due to imperfection in CSIR is not
significant, if the training power is chosen appropriately.Comment: Submitted to IEEE Transactions on Communications Jan 2007, Revised
Jun 2007, Revised Nov 200
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.
Copyright may be transferred without notice, after which this version may no
longer be accessibl
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
Beamforming Techniques for Non-Orthogonal Multiple Access in 5G Cellular Networks
In this paper, we develop various beamforming techniques for downlink
transmission for multiple-input single-output (MISO) non-orthogonal multiple
access (NOMA) systems. First, a beamforming approach with perfect channel state
information (CSI) is investigated to provide the required quality of service
(QoS) for all users. Taylor series approximation and semidefinite relaxation
(SDR) techniques are employed to reformulate the original non-convex power
minimization problem to a tractable one. Further, a fairness-based beamforming
approach is proposed through a max-min formulation to maintain fairness between
users. Next, we consider a robust scheme by incorporating channel
uncertainties, where the transmit power is minimized while satisfying the
outage probability requirement at each user. Through exploiting the SDR
approach, the original non-convex problem is reformulated in a linear matrix
inequality (LMI) form to obtain the optimal solution. Numerical results
demonstrate that the robust scheme can achieve better performance compared to
the non-robust scheme in terms of the rate satisfaction ratio. Further,
simulation results confirm that NOMA consumes a little over half transmit power
needed by OMA for the same data rate requirements. Hence, NOMA has the
potential to significantly improve the system performance in terms of transmit
power consumption in future 5G networks and beyond.Comment: accepted to publish in IEEE Transactions on Vehicular Technolog
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