1,177 research outputs found
Spectral Efficiency Analysis of Multi-Cell Massive MIMO Systems with Ricean Fading
This paper investigates the spectral efficiency of multi-cell massive
multiple-input multiple-output systems with Ricean fading that utilize the
linear maximal-ratio combining detector. We firstly present closed-form
expressions for the effective signal-to-interference-plus-noise ratio (SINR)
with the least squares and minimum mean squared error (MMSE) estimation
methods, respectively, which apply for any number of base-station antennas
and any Ricean -factor. Also, the obtained results can be particularized in
Rayleigh fading conditions when the Ricean -factor is equal to zero. In the
following, novel exact asymptotic expressions of the effective SINR are derived
in the high and high Ricean -factor regimes. The corresponding analysis
shows that pilot contamination is removed by the MMSE estimator when we
consider both infinite and infinite Ricean -factor, while the pilot
contamination phenomenon persists for the rest of cases. All the theoretical
results are verified via Monte-Carlo simulations.Comment: 15 pages, 2 figures, the tenth International Conference on Wireless
Communications and Signal Processing (WCSP 2018), to appea
On the Achievable Rates of Decentralized Equalization in Massive MU-MIMO Systems
Massive multi-user (MU) multiple-input multiple-output (MIMO) promises
significant gains in spectral efficiency compared to traditional, small-scale
MIMO technology. Linear equalization algorithms, such as zero forcing (ZF) or
minimum mean-square error (MMSE)-based methods, typically rely on centralized
processing at the base station (BS), which results in (i) excessively high
interconnect and chip input/output data rates, and (ii) high computational
complexity. In this paper, we investigate the achievable rates of decentralized
equalization that mitigates both of these issues. We consider two distinct BS
architectures that partition the antenna array into clusters, each associated
with independent radio-frequency chains and signal processing hardware, and the
results of each cluster are fused in a feedforward network. For both
architectures, we consider ZF, MMSE, and a novel, non-linear equalization
algorithm that builds upon approximate message passing (AMP), and we
theoretically analyze the achievable rates of these methods. Our results
demonstrate that decentralized equalization with our AMP-based methods incurs
no or only a negligible loss in terms of achievable rates compared to that of
centralized solutions.Comment: Will be presented at the 2017 IEEE International Symposium on
Information Theor
Jamming Resistant Receivers for Massive MIMO
We design jamming resistant receivers to enhance the robustness of a massive
MIMO uplink channel against jamming. In the pilot phase, we estimate not only
the desired channel, but also the jamming channel by exploiting purposely
unused pilot sequences. The jamming channel estimate is used to construct the
linear receive filter to reduce impact that jamming has on the achievable
rates. The performance of the proposed scheme is analytically and numerically
evaluated. These results show that the proposed scheme greatly improves the
rates, as compared to conventional receivers. Moreover, the proposed schemes
still work well with stronger jamming power.Comment: Accepted in the 42nd IEEE Int. Conf. Acoust., Speech, and Signal
Process. (ICASSP2017
Massive MIMO: How many antennas do we need?
We consider a multicell MIMO uplink channel where each base station (BS) is
equipped with a large number of antennas N. The BSs are assumed to estimate
their channels based on pilot sequences sent by the user terminals (UTs).
Recent work has shown that, as N grows infinitely large, (i) the simplest form
of user detection, i.e., the matched filter (MF), becomes optimal, (ii) the
transmit power per UT can be made arbitrarily small, (iii) the system
performance is limited by pilot contamination. The aim of this paper is to
assess to which extent the above conclusions hold true for large, but finite N.
In particular, we derive how many antennas per UT are needed to achieve \eta %
of the ultimate performance. We then study how much can be gained through more
sophisticated minimum-mean-square-error (MMSE) detection and how many more
antennas are needed with the MF to achieve the same performance. Our analysis
relies on novel results from random matrix theory which allow us to derive
tight approximations of achievable rates with a class of linear receivers.Comment: 6 pages, 3 figures, to be presented at the Allerton Conference on
Communication, Control and Computing, Urbana-Champaign, Illinois, US, Sep.
201
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