3,994 research outputs found
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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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
Alamouti OFDM/OQAM systems with time reversal technique
Orthogonal Frequency Division Multiplexing with Offset Quadrature Amplitude
Modulation (OFDM/OQAM) is a multicarrier modulation scheme that can be
considered as an alternative to the conventional Orthogonal Frequency Division
Multiplexing (OFDM) with Cyclic Prefix (CP) for transmission over multipath
fading channels. In this paper, we investigate the combination of the OFDM/OQAM
with Alamouti system with Time Reversal (TR) technique. TR can be viewed as a
precoding scheme which can be combined with OFDM/OQAM and easily carried out in
a Multiple Input Single Output (MISO) context such as Alamouti system. We
present the simulation results of the performance of OFDM/OQAM system in SISO
case compared with the conventional CP-OFDM system and the performance of the
combination Alamouti OFDM/OQAM with TR compared to Alamouti CP-OFDM. The
performance is derived by computing the Bit Error Rate (BER) as a function of
the transmit signal-to-noise ratio (SNR)
Formulating the Net Gain of MISO-SFN in the Presence of Self-Interferences
In this study, an analytical formula for multiple-input single-output single frequency network gain (MISO-SFNG) is investigated. To formulate the net MISO-SFNG, we derived the average signal to interference plus noise ratio (SINR) where the gain achieved by the distributed MISO diversity as a function of power imbalance is curve-fitted. Further, we analyzed the losses owing to self-interferences resulting from the delay spread and imperfect channel estimation. We verified the accuracy and effectiveness of the derived formula by comparing the measurement results with the analytical results. The derived formula helps to understand how various system factors affect the gain under a given condition. The formula can be used to evaluate the MISO-SFNG and to predict the MISO-SFN coverage in various system configurations
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