286 research outputs found
Performance Analysis of Massive MIMO-OFDM System Incorporated with Various Transforms for Image Communication in 5G Systems
Modern-day applications of fifth-generation (5G) and sixth-generation (6G) systems require fast, efficient, and robust transmission of multimedia information over wireless communication medium for both mobile and fixed users. The hybrid amalgamation of massive multiple input multiple output (mMIMO) and orthogonal frequency division multiplexing (OFDM) proves to be an impressive methodology for fulfilling the needs of 5G and 6G users. In this paper, the performance of the hybrid combination of massive MIMO and OFDM schemes augmented with fast Fourier transform (FFT), fractional Fourier transform (FrFT) or discrete wavelet transform (DWT) is evaluated to study their potential for reliable image communication. The analysis is carried over the Rayleigh fading channels and M-ary phase-shift keying (M-PSK) modulation schemes. The parameters used in our analysis to assess the outcome of proposed versions of OFDM-mMIMO include signal-to-noise ratio (SNR) vs. peak signal-to-noise ratio (PSNR) and SNR vs. structural similarity index measure (SSIM) at the receiver. Our results indicate that massive MIMO systems incorporating FrFT and DWT can lead to higher PSNR and SSIM values for a given SNR and number of users, when compared with in contrast to FFT-based massive MIMO-OFDM systems under the same conditions.publishersversionpublishe
Joint Antenna Selection and Phase-Only Beamforming Using Mixed-Integer Nonlinear Programming
In this paper, we consider the problem of joint antenna selection and analog
beamformer design in downlink single-group multicast networks. Our objective is
to reduce the hardware costs by minimizing the number of required phase
shifters at the transmitter while fulfilling given distortion limits at the
receivers. We formulate the problem as an L0 minimization problem and devise a
novel branch-and-cut based algorithm to solve the resulting mixed-integer
nonlinear program to optimality. We also propose a suboptimal heuristic
algorithm to solve the above problem approximately with a low computational
complexity. Computational results illustrate that the solutions produced by the
proposed heuristic algorithm are optimal in most cases. The results also
indicate that the performance of the optimal methods can be significantly
improved by initializing with the result of the suboptimal method.Comment: to be presented at WSA 201
Quantifying Potential Energy Efficiency Gain in Green Cellular Wireless Networks
Conventional cellular wireless networks were designed with the purpose of
providing high throughput for the user and high capacity for the service
provider, without any provisions of energy efficiency. As a result, these
networks have an enormous Carbon footprint. In this paper, we describe the
sources of the inefficiencies in such networks. First we present results of the
studies on how much Carbon footprint such networks generate. We also discuss
how much more mobile traffic is expected to increase so that this Carbon
footprint will even increase tremendously more. We then discuss specific
sources of inefficiency and potential sources of improvement at the physical
layer as well as at higher layers of the communication protocol hierarchy. In
particular, considering that most of the energy inefficiency in cellular
wireless networks is at the base stations, we discuss multi-tier networks and
point to the potential of exploiting mobility patterns in order to use base
station energy judiciously. We then investigate potential methods to reduce
this inefficiency and quantify their individual contributions. By a
consideration of the combination of all potential gains, we conclude that an
improvement in energy consumption in cellular wireless networks by two orders
of magnitude, or even more, is possible.Comment: arXiv admin note: text overlap with arXiv:1210.843
Massive MIMO transmission techniques
Next generation of mobile communication systems must support astounding data traffic increases, higher data rates and lower latency, among other requirements. These requirements should be met while assuring energy efficiency for mobile devices and base stations.
Several technologies are being proposed for 5G, but a consensus begins to emerge. Most likely, the future core 5G technologies will include massive MIMO (Multiple Input Multiple Output) and beamforming schemes operating in the millimeter wave spectrum. As soon as the millimeter wave propagation difficulties are overcome, the full potential of massive MIMO structures can be tapped.
The present work proposes a new transmission system with bi-dimensional antenna arrays working at millimeter wave frequencies, where the multiple antenna configurations can be used to obtain very high gain and directive transmission in point to point communications. A combination of beamforming with a constellation shaping scheme is proposed, that enables good user isolation and protection against eavesdropping, while simultaneously assuring power efficient amplification of multi-level constellations
Coordinated Per-Antenna Power Minimization for Multicell Massive MIMO Systems with Low-Resolution Data Converters
A multicell-coordinated beamforming solution for massive multiple-input
multiple-output orthogonal frequency-division multiplexing (OFDM) systems is
presented when employing low-resolution data converters and per-antenna level
constraints. For a more realistic deployment, we aim to find the downlink (DL)
beamformer that minimizes the maximum power on transmit antenna array of each
basestation under received signal quality constraints while minimizing
per-antenna transmit power. We show that strong duality holds between the
primal DL formulation and its manageable Lagrangian dual problem which can be
interpreted as the virtual uplink (UL) problem with adjustable noise covariance
matrices. For a fixed set of noise covariance matrices, we claim that the
virtual UL solution is effectively used to compute the DL beamformer and noise
covariance matrices can be subsequently updated with an associated subgradient.
Our primary contributions are then (1) formulating the quantized DL OFDM
antenna power minimax problem and deriving its associated dual problem, (2)
showing strong duality and interpreting the dual as a virtual quantized UL OFDM
problem, and (3) developing an iterative minimax algorithm based on the dual
problem. Simulations validate the proposed algorithm in terms of the maximum
antenna transmit power and peak-to-average-power ratio.Comment: submitted for possible IEEE journal publicatio
Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions
Interference is traditionally viewed as a performance limiting factor in wireless communication systems, which is to be minimized or mitigated. Nevertheless, a recent line of work has shown that by manipulating the interfering signals such that they add up constructively at the receiver side, known interference can be made beneficial and further improve the system performance in a variety of wireless scenarios, achieved by symbol-level precoding (SLP). This paper aims to provide a tutorial on interference exploitation techniques from the perspective of precoding design in a multi-antenna wireless communication system, by beginning with the classification of constructive interference (CI) and destructive interference (DI). The definition for CI is presented and the corresponding mathematical characterization is formulated for popular modulation types, based on which optimization-based precoding techniques are discussed. In addition, the extension of CI precoding to other application scenarios as well as for hardware efficiency is also described. Proof-of-concept testbeds are demonstrated for the potential practical implementation of CI precoding, and finally a list of open problems and practical challenges are presented to inspire and motivate further research directions in this area
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