2,099 research outputs found
Secret-key generation from wireless channels: Mind the reflections
Secret-key generation in a wireless environment exploiting the randomness and
reciprocity of the channel gains is considered. A new channel model is proposed
which takes into account the effect of reflections (or re-radiations) from
receive antenna elements, thus capturing an physical property of practical
antennas. It turns out that the reflections have a deteriorating effect on the
achievable secret-key rate between the legitimate nodes at high
signal-to-noise-power-ratio (SNR). The insights provide guidelines in the
design and operation of communication systems using the properties of the
wireless channel to prevent eavesdropping.Comment: 6 pages, 9 figure
Antenna Impedance Estimation at MIMO Receivers
This paper considers antenna impedance estimation based on training sequences
at MIMO receivers. The goal is to firstly leverage extensive resources
available in most wireless systems for channel estimation to estimate antenna
impedance in real-time. We assume the receiver switches its impedance in a
predetermined fashion during each training sequence. Based on voltage
observation across the load, a classical estimation framework is developed
incorporating the Rayleigh fading assumption. We then derive in closed-form a
maximum-likelihood (ML) estimator under i.i.d. fading and show this same ML
estimator is a method of moments (MM) estimator in correlated channels.
Numerical results suggest a fast algorithm, i.e., MLE in i.i.d. fading and the
MM estimator in correlated fading, that estimates the unknown antenna impedance
in real-time for all Rayleigh fading channels.Comment: 31 pages, 6 figure
Impedance Variation Detection at MISO Receivers
Techniques have been proposed to estimate unknown antenna impedance due to
time-varying near-field loading conditions at multiple-input single-output
(MISO) receivers. However, it remains unclear when a change occurs and
impedance estimation becomes necessary. In this letter, we address this problem
by formulating it as a hypothesis test. Our contributions include deriving a
generalized likelihood-ratio test (GLRT) detector to decide if the antenna
impedance has changed over two groups of packets. This GLRT formulation leads
to a novel optimization problem, but we propose a binary search based algorithm
to solve it efficiently. Our derived GLRT detector enjoys a better detection
and false alarm trade-off when compared with a well-known, reference detector
in simulations. As one result, more transmit diversity significantly improves
detection accuracy at a given false alarm rate, especially in slow fading
channels.Comment: 5 pages, 2 figures, journa
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
A Study on MIMO Wireless Communication Channel Performance in Correlated Channels
MIMO wireless communication system is gaining popularity by days due to its versatility and wide applicability. When signal travels through wireless link it gets affected due to the disturbances present in the channel i.e. different sorts of interference and noise. Plus because there may or may not be a Line of sight (LOS) path between transmitter and receiver signal copies leaving the transmitter at the same time reaches the receiver with different delays and attenuation due to multiple reflections and interfere with each other at the receiver. Therefore fading of received signal power is also observed in case of a wireless MIMO link. In case of wireless two most important objectives can be channel estimation and signal detection. The importance of the wireless channel estimation can be attributed to faithful signal detection and transmit beam forming, power allocation etc. when Channel state information (CSI) is communicated to the transmitter via feedback loop in case of uni-directional channel or by simultaneous estimation by the transmitter itself in case of bi-directional channel. This text introduces some aspects of signal detection and mostly different aspects of channel estimation and explains why it is important in context of signal detection, beam forming etc. A brief introduction to antenna arrays and beam forming procedures have been given here. The cause of occurrence of spatial and temporal correlations have been discussed and different ways of modelling the spatial and temporal correlations involved are also briefly introduced in this text. How different link and link-end properties e.g. antenna spacing, angular spread of radiation beam, mean angle of radiation, mutual coupling present between elements of an antenna array etc. affects the channel correlations thereby affecting the performance of the MIMO wireless communication channel. Modelling of antenna mutual coupling and different estimation and compensation techniques are also discussed here
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