167 research outputs found
Sensing Aided OTFS Channel Estimation for Massive MIMO Systems
Orthogonal time frequency space (OTFS) modulation has the potential to enable
robust communications in highly-mobile scenarios. Estimating the channels for
OTFS systems, however, is associated with high pilot signaling overhead that
scales with the maximum delay and Doppler spreads. This becomes particularly
challenging for massive MIMO systems where the overhead also scales with the
number of antennas. An important observation however is that the delay,
Doppler, and angle of departure/arrival information are directly related to the
distance, velocity, and direction information of the mobile user and the
various scatterers in the environment. With this motivation, we propose to
leverage radar sensing to obtain this information about the mobile users and
scatterers in the environment and leverage it to aid the OTFS channel
estimation in massive MIMO systems.
As one approach to realize our vision, this paper formulates the OTFS channel
estimation problem in massive MIMO systems as a sparse recovery problem and
utilizes the radar sensing information to determine the support (locations of
the non-zero delay-Doppler taps). The proposed radar sensing aided sparse
recovery algorithm is evaluated based on an accurate 3D ray-tracing framework
with co-existing radar and communication data. The results show that the
developed sensing-aided solution consistently outperforms the standard sparse
recovery algorithms (that do not leverage radar sensing data) and leads to a
significant reduction in the pilot overhead, which highlights a promising
direction for OTFS based massive MIMO systems.Comment: submitted to IEE
OTFS-NOMA: An Efficient Approach for Exploiting Heterogenous User Mobility Profiles
This paper considers a challenging communication scenario, in which users
have heterogenous mobility profiles, e.g., some users are moving at high speeds
and some users are static. A new non-orthogonal multiple-access (NOMA)
transmission protocol that incorporates orthogonal time frequency space (OTFS)
modulation is proposed. Thereby, users with different mobility profiles are
grouped together for the implementation of NOMA. The proposed OTFS-NOMA
protocol is shown to be applicable to both uplink and downlink transmission,
where sophisticated transmit and receive strategies are developed to remove
inter-symbol interference and harvest both multi-path and multi-user diversity.
Analytical results demonstrate that both the high-mobility and low-mobility
users benefit from the application of OTFS-NOMA. In particular, the use of NOMA
allows the spreading of the high-mobility users' signals over a large amount of
time-frequency resources, which enhances the OTFS resolution and improves the
detection reliability. In addition, OTFS-NOMA ensures that low-mobility users
have access to bandwidth resources which in conventional OTFS-orthogonal
multiple access (OTFS-NOMA) would be solely occupied by the high-mobility
users. Thus, OTFS-NOMA improves the spectral efficiency and reduces latency
How to Combine OTFS and OFDM Modulations in Massive MIMO?
In this paper, we consider a downlink (DL) massive multiple-input
multiple-output (MIMO) system, where different users have different mobility
profiles. To support this system, we propose to use a hybrid orthogonal time
frequency space (OTFS)/orthogonal frequency division multiplexing (OFDM)
modulation scheme, where OTFS is applied for high-mobility users and OFDM is
used for low-mobility users. Two precoding designs, namely full zero-forcing
(FZF) precoding and partial zero-forcing (PZF) precoding, are considered and
analyzed in terms of per-user spectral efficiency (SE). With FZF, interference
among users is totally eliminated at the cost of high computational complexity,
while PZF can be used to provide a trade-off between complexity and
performance. To apply PZF precoding, users are grouped into two disjoint groups
according to their mobility profile or channel gain. Then, zero-forcing (ZF) is
utilized for high-mobility or strong channel gain users to completely cancel
the inter-group interference, while maximum ratio transmission (MRT) is applied
for low-mobility users or users with weak channel gain. To shed light on the
system performance, the SE for high-mobility and low-mobility users with a
minimum-mean-square-error (MMSE)-successive interference cancellation (SIC)
detector is investigated. Our numerical results reveal that the PZF precoding
with channel gain grouping can guarantee a similar quality of service for all
users. In addition, with mobility-based grouping, the hybrid OTFS/OFDM
modulation outperforms the conventional OFDM modulation for high-mobility
users
Active Terminal Identification, Channel Estimation, and Signal Detection for Grant-Free NOMA-OTFS in LEO Satellite Internet-of-Things
This paper investigates the massive connectivity of low Earth orbit (LEO)
satellite-based Internet-of-Things (IoT) for seamless global coverage. We
propose to integrate the grant-free non-orthogonal multiple access (GF-NOMA)
paradigm with the emerging orthogonal time frequency space (OTFS) modulation to
accommodate the massive IoT access, and mitigate the long round-trip latency
and severe Doppler effect of terrestrial-satellite links (TSLs). On this basis,
we put forward a two-stage successive active terminal identification (ATI) and
channel estimation (CE) scheme as well as a low-complexity multi-user signal
detection (SD) method. Specifically, at the first stage, the proposed training
sequence aided OTFS (TS-OTFS) data frame structure facilitates the joint ATI
and coarse CE, whereby both the traffic sparsity of terrestrial IoT terminals
and the sparse channel impulse response are leveraged for enhanced performance.
Moreover, based on the single Doppler shift property for each TSL and sparsity
of delay-Doppler domain channel, we develop a parametric approach to further
refine the CE performance. Finally, a least square based parallel time domain
SD method is developed to detect the OTFS signals with relatively low
complexity. Simulation results demonstrate the superiority of the proposed
methods over the state-of-the-art solutions in terms of ATI, CE, and SD
performance confronted with the long round-trip latency and severe Doppler
effect.Comment: 20 pages, 9 figures, accepted by IEEE Transactions on Wireless
Communication
Low-Complexity Iterative Detection for Orthogonal Time Frequency Space Modulation
We elaborate on the recently proposed orthogonal time frequency space (OTFS)
modulation technique, which provides significant advantages over orthogonal
frequency division multiplexing (OFDM) in Doppler channels. We first derive the
input--output relation describing OTFS modulation and demodulation (mod/demod)
for delay--Doppler channels with arbitrary number of paths, with given delay
and Doppler values. We then propose a low-complexity message passing (MP)
detection algorithm, which is suitable for large-scale OTFS taking advantage of
the inherent channel sparsity. Since the fractional Doppler paths (i.e., not
exactly aligned with the Doppler taps) produce the inter Doppler interference
(IDI), we adapt the MP detection algorithm to compensate for the effect of IDI
in order to further improve performance. Simulations results illustrate the
superior performance gains of OTFS over OFDM under various channel conditions.Comment: 6 pages, 7 figure
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