48 research outputs found
Achievable Rates and Training Overheads for a Measured LOS Massive MIMO Channel
This paper presents achievable uplink (UL) sumrate predictions for a measured
line-of-sight (LOS) massive multiple-input, multiple-output (MIMO) (MMIMO)
scenario and illustrates the trade-off between spatial multiplexing performance
and channel de-coherence rate for an increasing number of base station (BS)
antennas. In addition, an orthogonal frequency division multiplexing (OFDM)
case study is formed which considers the 90% coherence time to evaluate the
impact of MMIMO channel training overheads in high-speed LOS scenarios. It is
shown that whilst 25% of the achievable zero-forcing (ZF) sumrate is lost when
the resounding interval is increased by a factor of 4, the OFDM training
overheads for a 100-antenna MMIMO BS using an LTE-like physical layer could be
as low as 2% for a terminal speed of 90m/s.Comment: 4 pages, 5 figure
Impact of User Mobility on Optimal Linear Receivers in Cellular Networks
We consider the uplink of non-cooperative multi-cellular systems deploying
multiple antenna elements at the base stations (BS), covering both the cases of
conventional and very large number of antennas. Given the inevitable pilot
contamination and an arbitrary path-loss for each link, we address the impact
of time variation of the channel due to the relative movement between users and
BS antennas, which limits system's performance even if the number antennas is
increased, as shown. In particular, we propose an optimal linear receiver (OLR)
maximizing the received signal-to-interference-plus-noise (SINR). Closed-form
lower and upper bounds are derived as well as the deterministic equivalent of
the OLR is obtained. Numerical results reveal the outperformance of the
proposed OLR against known linear receivers, mostly in environments with high
interference and certain user mobility, as well as that massive MIMO is
preferable even in time-varying channel conditions.Comment: 3 figures, 6 pages, accepted in ICC 201
Special Issue on Massive MIMO
International audienceDemand for wireless communications is projected to grow by more than a factor of forty or more over the next five years. A potential technology for meeting this demand is Massive MIMO (also called Large-Scale Antenna Systems, Large-Scale MIMO, ARGOS, Full-Dimension MIMO, or Hyper-MIMO), a form of multi-user multipleantenna wireless which promises orders-of-magnitude improvements in spectral-efficiency over 4G technology, and accompanying improvements in radiated energy-efficiency. The distinguishing feature of Massive MIMO is that a large number of service-antennas - possibly hundreds or even thousands - work for a significantly smaller number of active autonomous terminals. Upsetting the traditional parity between service antennas and terminals in this manner is a game-changer: The simplest multiplexing pre-coding and de-coding algorithms can be nearly optimal, expensive ultra-linear forty-Watt power amplifiers are replaced by many low-power units, and the favorable action of the law of large numbers can greatly facilitate power-control and resource-allocation. Massive MIMO is still an emerging field. There are many unanswered theoretical questions and much remains to be done to obtain a reduction to practice. The six papers in this Special Issue are a sampling of the types of problems that are topics of active research. The papers logically fall into three categories: a) Acquisition of Channel State Information, b) Spatial Multiplexing Algorithms, and c) Massive Array Issues and Architectures
Wireless channel-based ciphering key generation: effect of aging and treatment
Key generation for data cryptography is vital in wireless communications security. This key must be generated in a random way so that can not be regenerated by a third party other than the intended receiver. The random nature of the wireless channel is utilized to generate the encryption key. However, the randomness of wireless channels deteriorated over time due to channel aging which casing security threats, particularly for spatially correlated channels. In this paper, the effect of channel aging on the ciphering key generations is addressed. A proposed method to randomize the encryption key each coherence time is developed which decreases the correlation between keys generated at consecutive coherence times. When compared to the conventional method, the randomness improvement is significant at each time interval. The simulation results show that the proposed method improves the randomness of the encrypting keys
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
Design and Performance Analysis of Non-Coherent Detection Systems with Massive Receiver Arrays
Harvesting the gain of a large number of antennas in a mmWave band has mainly
been relying on the costly operation of channel state information (CSI)
acquisition and cumbersome phase shifters. Recent works have started to
investigate the possibility to use receivers based on energy detection (ED),
where a single data stream is decoded based on the channel and noise energy.
The asymptotic features of the massive receiver array lead to a system where
the impact of the noise becomes predictable due to a noise hardening effect.
This in effect extends the communication range compared to the receiver with a
small number of antennas, as the latter is limited by the unpredictability of
the additive noise. When the channel has a large number of spatial degrees of
freedom, the system becomes robust to imperfect channel knowledge due to
channel hardening. We propose two detection methods based on the instantaneous
and average channel energy, respectively. Meanwhile, we design the detection
thresholds based on the asymptotic properties of the received energy.
Differently from existing works, we analyze the scaling law behavior of the
symbol-error-rate (SER). When the instantaneous channel energy is known, the
performance of ED approaches that of the coherent detection in high SNR
scenarios. When the receiver relies on the average channel energy, our
performance analysis is based on the exact SER, rather than an approximation.
It is shown that the logarithm of SER decreases linearly as a function of the
number of antennas. Additionally, a saturation appears at high SNR for PAM
constellations of order larger than two, due to the uncertainty on the channel
energy. Simulation results show that ED, with a much lower complexity, achieves
promising performance both in Rayleigh fading channels and in sparse channels