701 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
Channel Estimation for LEO Satellite Massive MIMO OFDM Communications
In this paper, we investigate the massive multiple-input multiple-output
orthogonal frequency division multiplexing channel estimation for
low-earth-orbit satellite communication systems. First, we use the angle-delay
domain channel to characterize the space-frequency domain channel. Then, we
show that the asymptotic minimum mean square error (MMSE) of the channel
estimation can be minimized if the array response vectors of the user terminals
(UTs) that use the same pilot are orthogonal. Inspired by this, we design an
efficient graph-based pilot allocation strategy to enhance the channel
estimation performance. In addition, we devise a novel two-stage channel
estimation (TSCE) approach, in which the received signals at the satellite are
manipulated with per-subcarrier space domain processing followed by per-user
frequency domain processing. Moreover, the space domain processing of each UT
is shown to be identical for all the subcarriers, and an asymptotically optimal
vector for the per-subcarrier space domain linear processing is derived. The
frequency domain processing can be efficiently implemented by means of the fast
Toeplitz system solver. Simulation results show that the proposed TSCE approach
can achieve a near performance to the MMSE estimation with much lower
complexity.Comment: accepted by IEEE Transactions on Wireless Communication
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