3,070 research outputs found
Spectral and Energy Efficiency of IRS-Assisted MISO Communication with Hardware Impairments
In this letter, we analyze the spectral and energy efficiency of an intelligent reflecting surface (IRS)-assisted multiple-input single-output (MISO) downlink system with hardware impairments. An extended error vector magnitude (EEVM) model is utilized to characterize the impact of radio-frequency (RF) impairments at the access point (AP) and phase noise is considered at the IRS. We show that the spectral efficiency is limited due to the hardware impairments even when the numbers of AP antennas and IRS elements grow infinitely large, which is in contrast with the conventional case with ideal hardware. Moreover, the performance degradation at high SNR is shown to be mainly affected by the AP hardware impairments rather than by the phase noise at the IRS. We further obtain in closed form the optimal transmit power for energy efficiency maximization. Simulation results are provided to verify the obtained results
Beamforming Designs and Performance Evaluations for Intelligent Reflecting Surface Enhanced Wireless Communication System with Hardware Impairments
Intelligent reflecting surface (IRS) can effectively control the wavefront of
the impinging signals, and has emerged as a promising way to improve the energy
and spectrum efficiency of wireless communication systems. Most existing
studies were conducted with an assumption that the hardware operations are
perfect without any impairment. However, both physical transceiver and IRS
suffer from non-negligible hardware impairments in practice, which will bring
some major challenges, e.g., increasing the difficulty and complexity of the
beamforming designs, and degrading the system performance. In this paper, by
taking hardware impairments into consideration, we make the transmit and
reflect beamforming designs and evaluate the system performance. First, we
utilize the linear minimum mean square error estimator to make the channel
estimations, and analyze the factors that affect estimation accuracy. Then, we
derive the optimal transmit beamforming vector, and propose a gradient descent
method-based algorithm to obtain a sub-optimal reflect beamforming solution.
Next, we analyze the asymptotic channel capacities by considering two types of
asymptotics with respect to the transmit power and the numbers of antennas and
reflecting elements. Finally, we analyze the power scaling law and the energy
efficiency. By comparing the performance of our proposed algorithm with the
upper bound on the performance of global optimal reflect beamforming solution,
the simulation results demonstrate that our proposed algorithm can offer an
outstanding performance with low computational complexity. The simulation
results also show that there is no need to cost a lot on expensive antennas to
achieve both high spectral efficiency and energy efficiency when the
communication system is assisted by an IRS and suffer from hardware
impairments.Comment: arXiv admin note: text overlap with arXiv:2004.09804,
arXiv:2004.0976
RIS-Aided MIMO Systems with Hardware Impairments: Robust Beamforming Design and Analysis
Reconfigurable intelligent surface (RIS) has been anticipated to be a novel
cost-effective technology to improve the performance of future wireless
systems. In this paper, we investigate a practical RIS-aided
multiple-input-multiple-output (MIMO) system in the presence of transceiver
hardware impairments, RIS phase noise and imperfect channel state information
(CSI). Joint design of the MIMO transceiver and RIS reflection matrix to
minimize the total average mean-square-error (MSE) of all data streams is
particularly considered. This joint design problem is non-convex and
challenging to solve due to the newly considered practical imperfections. To
tackle the issue, we first analyze the total average MSE by incorporating the
impacts of the above system imperfections. Then, in order to handle the tightly
coupled optimization variables and non-convex NP-hard constraints, an efficient
iterative algorithm based on alternating optimization (AO) framework is
proposed with guaranteed convergence, where each subproblem admits a
closed-form optimal solution by leveraging the majorization-minimization (MM)
technique. Moreover, via exploiting the special structure of the unit-modulus
constraints, we propose a modified Riemannian gradient ascent (RGA) algorithm
for the discrete RIS phase shift optimization. Furthermore, the optimality of
the proposed algorithm is validated under line-of-sight (LoS) channel
conditions, and the irreducible MSE floor effect induced by imperfections of
both hardware and CSI is also revealed in the high signal-to-noise ratio (SNR)
regime. Numerical results show the superior MSE performance of our proposed
algorithm over the adopted benchmark schemes, and demonstrate that increasing
the number of RIS elements is not always beneficial under the above system
imperfections.Comment: 30 pages, 8 figures. This paper has been submitted to IEEE journal
for possible publicatio
Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays
Massive MIMO (multiple-input multiple-output) is no longer a "wild" or
"promising" concept for future cellular networks - in 2018 it became a reality.
Base stations (BSs) with 64 fully digital transceiver chains were commercially
deployed in several countries, the key ingredients of Massive MIMO have made it
into the 5G standard, the signal processing methods required to achieve
unprecedented spectral efficiency have been developed, and the limitation due
to pilot contamination has been resolved. Even the development of fully digital
Massive MIMO arrays for mmWave frequencies - once viewed prohibitively
complicated and costly - is well underway. In a few years, Massive MIMO with
fully digital transceivers will be a mainstream feature at both sub-6 GHz and
mmWave frequencies. In this paper, we explain how the first chapter of the
Massive MIMO research saga has come to an end, while the story has just begun.
The coming wide-scale deployment of BSs with massive antenna arrays opens the
door to a brand new world where spatial processing capabilities are
omnipresent. In addition to mobile broadband services, the antennas can be used
for other communication applications, such as low-power machine-type or
ultra-reliable communications, as well as non-communication applications such
as radar, sensing and positioning. We outline five new Massive MIMO related
research directions: Extremely large aperture arrays, Holographic Massive MIMO,
Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive
MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin
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