857 research outputs found
Impact of Line-of-Sight and Unequal Spatial Correlation on Uplink MU-MIMO Systems
Closed-form approximations of the expected per-terminal
signal-to-interference-plus-noise-ratio (SINR) and ergodic sum spectral
efficiency of a multiuser multiple-input multiple-output system are presented.
Our analysis assumes spatially correlated Ricean fading channels with
maximum-ratio combining on the uplink. Unlike previous studies, our model
accounts for the presence of unequal correlation matrices, unequal Rice
factors, as well as unequal link gains to each terminal. The derived
approximations lend themselves to useful insights, special cases and
demonstrate the aggregate impact of line-of-sight (LoS) and unequal correlation
matrices. Numerical results show that while unequal correlation matrices
enhance the expected SINR and ergodic sum spectral efficiency, the presence of
strong LoS has an opposite effect. Our approximations are general and remain
insensitive to changes in the system dimensions, signal-to-noise-ratios, LoS
levels and unequal correlation levels.Comment: 4 pages, 2 figures, accepted for publication in the IEEE Wireless
Communications Letters, Vol. 6, 201
Uplink Analysis of Large MU-MIMO Systems With Space-Constrained Arrays in Ricean Fading
Closed-form approximations to the expected per-terminal
signal-to-interference-plus-noise-ratio (SINR) and ergodic sum spectral
efficiency of a large multiuser multiple-input multiple-output system are
presented. Our analysis assumes correlated Ricean fading with maximum ratio
combining on the uplink, where the base station (BS) is equipped with a uniform
linear array (ULA) with physical size restrictions. Unlike previous studies,
our model caters for the presence of unequal correlation matrices and unequal
Rice factors for each terminal. As the number of BS antennas grows without
bound, with a finite number of terminals, we derive the limiting expected
per-terminal SINR and ergodic sum spectral efficiency of the system. Our
findings suggest that with restrictions on the size of the ULA, the expected
SINR saturates with increasing operating signal-to-noise-ratio (SNR) and BS
antennas. Whilst unequal correlation matrices result in higher performance, the
presence of strong line-of-sight (LoS) has an opposite effect. Our analysis
accommodates changes in system dimensions, SNR, LoS levels, spatial correlation
levels and variations in fixed physical spacings of the BS array.Comment: 7 pages, 3 figures, accepted for publication in the proceedings of
IEEE ICC, to be held in Paris, France, May 201
A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles
In recent years, there has been a dramatic increase in the use of unmanned
aerial vehicles (UAVs), particularly for small UAVs, due to their affordable
prices, ease of availability, and ease of operability. Existing and future
applications of UAVs include remote surveillance and monitoring, relief
operations, package delivery, and communication backhaul infrastructure.
Additionally, UAVs are envisioned as an important component of 5G wireless
technology and beyond. The unique application scenarios for UAVs necessitate
accurate air-to-ground (AG) propagation channel models for designing and
evaluating UAV communication links for control/non-payload as well as payload
data transmissions. These AG propagation models have not been investigated in
detail when compared to terrestrial propagation models. In this paper, a
comprehensive survey is provided on available AG channel measurement campaigns,
large and small scale fading channel models, their limitations, and future
research directions for UAV communication scenarios
Dual-Polarized Ricean MIMO Channels: Modeling and Performance Assessment
In wireless communication systems, dual-polarized (DP) instead of
single-polarized (SP) multiple-input multiple-output (MIMO) transmission is
used to improve the spectral efficiency under certain conditions on the channel
and the signal-to-noise ratio (SNR). In order to identify these conditions, we
first propose a novel channel model for DP mobile Ricean MIMO channels for
which statistical channel parameters are readily obtained from a moment-based
channel decomposition. Second, we derive an approximation of the mutual
information (MI), which can be expressed as a function of those statistical
channel parameters. Based on this approximation, we characterize the required
SNR for a DP MIMO system to outperform an SP MIMO system in terms of the MI.
Finally, we apply our results to channel measurements at 2.53 GHz. We find
that, using the proposed channel decomposition and the approximation of the MI,
we are able to reproduce the (practically relevant) SNR values above which DP
MIMO systems outperform SP MIMO systems.Comment: submitted to the IEEE Transactions on Communication
Distributed Detection over Fading MACs with Multiple Antennas at the Fusion Center
A distributed detection problem over fading Gaussian multiple-access channels
is considered. Sensors observe a phenomenon and transmit their observations to
a fusion center using the amplify and forward scheme. The fusion center has
multiple antennas with different channel models considered between the sensors
and the fusion center, and different cases of channel state information are
assumed at the sensors. The performance is evaluated in terms of the error
exponent for each of these cases, where the effect of multiple antennas at the
fusion center is studied. It is shown that for zero-mean channels between the
sensors and the fusion center when there is no channel information at the
sensors, arbitrarily large gains in the error exponent can be obtained with
sufficient increase in the number of antennas at the fusion center. In stark
contrast, when there is channel information at the sensors, the gain in error
exponent due to having multiple antennas at the fusion center is shown to be no
more than a factor of (8/pi) for Rayleigh fading channels between the sensors
and the fusion center, independent of the number of antennas at the fusion
center, or correlation among noise samples across sensors. Scaling laws for
such gains are also provided when both sensors and antennas are increased
simultaneously. Simple practical schemes and a numerical method using
semidefinite relaxation techniques are presented that utilize the limited
possible gains available. Simulations are used to establish the accuracy of the
results.Comment: 21 pages, 9 figures, submitted to the IEEE Transactions on Signal
Processin
Does Massive MIMO Fail in Ricean Channels?
Massive multiple-input multiple-output (MIMO) is now making its way to the
standardization exercise of future 5G networks. Yet, there are still
fundamental questions pertaining to the robustness of massive MIMO against
physically detrimental propagation conditions. On these grounds, we identify
scenarios under which massive MIMO can potentially fail in Ricean channels, and
characterize them physically, as well as, mathematically. Our analysis extends
and generalizes a stream of recent papers on this topic and articulates
emphatically that such harmful scenarios in Ricean fading conditions are
unlikely and can be compensated using any standard scheduling scheme. This
implies that massive MIMO is intrinsically effective at combating interuser
interference and, if needed, can avail of the base-station scheduler for
further robustness.Comment: IEEE Wireless Communications Letters, accepte
A Simple Cooperative Diversity Method Based on Network Path Selection
Cooperative diversity has been recently proposed as a way to form virtual
antenna arrays that provide dramatic gains in slow fading wireless
environments. However most of the proposed solutions require distributed
space-time coding algorithms, the careful design of which is left for future
investigation if there is more than one cooperative relay. We propose a novel
scheme, that alleviates these problems and provides diversity gains on the
order of the number of relays in the network. Our scheme first selects the best
relay from a set of M available relays and then uses this best relay for
cooperation between the source and the destination. We develop and analyze a
distributed method to select the best relay that requires no topology
information and is based on local measurements of the instantaneous channel
conditions. This method also requires no explicit communication among the
relays. The success (or failure) to select the best available path depends on
the statistics of the wireless channel, and a methodology to evaluate
performance for any kind of wireless channel statistics, is provided.
Information theoretic analysis of outage probability shows that our scheme
achieves the same diversity-multiplexing tradeoff as achieved by more complex
protocols, where coordination and distributed space-time coding for M nodes is
required, such as those proposed in [7]. The simplicity of the technique,
allows for immediate implementation in existing radio hardware and its adoption
could provide for improved flexibility, reliability and efficiency in future 4G
wireless systems.Comment: To appear, IEEE JSAC, special issue on 4
Maximum likelihood receivers for space-time coded MIMO systems with gaussian estimation errors
Maximum likelihood (ML) receivers for space-time coded multiple-input multiple-output (MIMO) systems with Gaussian channel estimation errors are proposed. Two different cases are considered. In the first case, the conditional probability density function (PDF) of the channel estimate is assumed Gaussian and known. In the second case, the joint PDF of the channel estimate and the true channel gain is assumed Gaussian and known. In addition to ML signal detection for space-time coded MIMO with ML and minimum mean-squared-error channel estimation, ML signal detection without channel estimation is also studied. Two suboptimal structures are derived. The Alamouti space-time codes are used to examine the performances of the new receivers. Simulation results show that the new receivers can reduce the gap between the conventional receiver with channel estimation errors and the receiver with perfect channel knowledge at least by half in some cases
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