247 research outputs found
Enhancing massive MIMO: A new approach for Uplink training based on heterogeneous coherence time
Massive multiple-input multiple-output (MIMO) is one of the key technologies
in future generation networks. Owing to their considerable spectral and energy
efficiency gains, massive MIMO systems provide the needed performance to cope
with the ever increasing wireless capacity demand. Nevertheless, the number of
scheduled users stays limited in massive MIMO both in time division duplexing
(TDD) and frequency division duplexing (FDD) systems. This is due to the
limited coherence time, in TDD systems, and to limited feedback capacity, in
FDD mode. In current systems, the time slot duration in TDD mode is the same
for all users. This is a suboptimal approach since users are subject to
heterogeneous Doppler spreads and, consequently, different coherence times. In
this paper, we investigate a massive MIMO system operating in TDD mode in
which, the frequency of uplink training differs among users based on their
actual channel coherence times. We argue that optimizing uplink training by
exploiting this diversity can lead to considerable spectral efficiency gain. We
then provide a user scheduling algorithm that exploits a coherence interval
based grouping in order to maximize the achievable weighted sum rate
Power Control in Massive MIMO with Dynamic User Population
This paper considers the problem of power control in Massive MIMO systems
taking into account the pilot contamination issue and the arrivals and
departures of users in the network. Contrary to most of existing work in MIMO
systems that focuses on the physical layer with fixed number of users, we
consider in this work that the users arrive dynamically and leave the network
once they are served. We provide a power control strategy, having a polynomial
complexity, and prove that this policy stabilizes the network whenever
possible. We then provide a distributed implementation of the power control
policy requiring low information exchange between the BSs and show that it
achieves the same stability region as the centralized policy.Comment: conference paper, submitte
Spectral Efficiency and Energy Efficiency Tradeoff in Massive MIMO Downlink Transmission with Statistical CSIT
As a key technology for future wireless networks, massive multiple-input
multiple-output (MIMO) can significantly improve the energy efficiency (EE) and
spectral efficiency (SE), and the performance is highly dependant on the degree
of the available channel state information (CSI). While most existing works on
massive MIMO focused on the case where the instantaneous CSI at the transmitter
(CSIT) is available, it is usually not an easy task to obtain precise
instantaneous CSIT. In this paper, we investigate EE-SE tradeoff in single-cell
massive MIMO downlink transmission with statistical CSIT. To this end, we aim
to optimize the system resource efficiency (RE), which is capable of striking
an EE-SE balance. We first figure out a closed-form solution for the
eigenvectors of the optimal transmit covariance matrices of different user
terminals, which indicates that beam domain is in favor of performing RE
optimal transmission in massive MIMO downlink. Based on this insight, the RE
optimization precoding design is reduced to a real-valued power allocation
problem. Exploiting the techniques of sequential optimization and random matrix
theory, we further propose a low-complexity suboptimal two-layer
water-filling-structured power allocation algorithm. Numerical results
illustrate the effectiveness and near-optimal performance of the proposed
statistical CSI aided RE optimization approach.Comment: Typos corrected. 14 pages, 7 figures. Accepted for publication on
IEEE Transactions on Signal Processing. arXiv admin note: text overlap with
arXiv:2002.0488
Amplitude Prediction from Uplink to Downlink CSI against Receiver Distortion in FDD Systems
In frequency division duplex (FDD) massive multiple-input multiple-output
(mMIMO) systems, the reciprocity mismatch caused by receiver distortion
seriously degrades the amplitude prediction performance of channel state
information (CSI). To tackle this issue, from the perspective of distortion
suppression and reciprocity calibration, a lightweight neural network-based
amplitude prediction method is proposed in this paper. Specifically, with the
receiver distortion at the base station (BS), conventional methods are employed
to extract the amplitude feature of uplink CSI. Then, learning along the
direction of the uplink wireless propagation channel, a dedicated and
lightweight distortion-learning network (Dist-LeaNet) is designed to restrain
the receiver distortion and calibrate the amplitude reciprocity between the
uplink and downlink CSI. Subsequently, by cascading, a single hidden
layer-based amplitude-prediction network (Amp-PreNet) is developed to
accomplish amplitude prediction of downlink CSI based on the strong amplitude
reciprocity. Simulation results show that, considering the receiver distortion
in FDD systems, the proposed scheme effectively improves the amplitude
prediction accuracy of downlink CSI while reducing the transmission and
processing delay.Comment: 10 pages, 5 figure
Temporal Analysis of Measured LOS Massive MIMO Channels with Mobility
The first measured results for massive multiple-input, multiple-output (MIMO)
performance in a line-of-sight (LOS) scenario with moderate mobility are
presented, with 8 users served by a 100 antenna base Station (BS) at 3.7 GHz.
When such a large number of channels dynamically change, the inherent
propagation and processing delay has a critical relationship with the rate of
change, as the use of outdated channel information can result in severe
detection and precoding inaccuracies. For the downlink (DL) in particular, a
time division duplex (TDD) configuration synonymous with massive MIMO
deployments could mean only the uplink (UL) is usable in extreme cases.
Therefore, it is of great interest to investigate the impact of mobility on
massive MIMO performance and consider ways to combat the potential limitations.
In a mobile scenario with moving cars and pedestrians, the correlation of the
MIMO channel vector over time is inspected for vehicles moving up to 29 km/h.
For a 100 antenna system, it is found that the channel state information (CSI)
update rate requirement may increase by 7 times when compared to an 8 antenna
system, whilst the power control update rate could be decreased by at least 5
times relative to a single antenna system.Comment: Accepted for presentation at the 85th IEEE Vehicular Technology
Conference in Sydney. 5 Pages. arXiv admin note: substantial text overlap
with arXiv:1701.0881
- …