2,121 research outputs found
A Novel Data-Aided Channel Estimation with Reduced Complexity for TDS-OFDM Systems
In contrast to the classical cyclic prefix (CP)-OFDM, the time domain
synchronous (TDS)-OFDM employs a known pseudo noise (PN) sequence as guard
interval (GI). Conventional channel estimation methods for TDS-OFDM are based
on the exploitation of the PN sequence and consequently suffer from intersymbol
interference (ISI). This paper proposes a novel dataaided channel estimation
method which combines the channel estimates obtained from the PN sequence and,
most importantly, additional channel estimates extracted from OFDM data
symbols. Data-aided channel estimation is carried out using the rebuilt OFDM
data symbols as virtual training sequences. In contrast to the classical turbo
channel estimation, interleaving and decoding functions are not included in the
feedback loop when rebuilding OFDM data symbols thereby reducing the
complexity. Several improved techniques are proposed to refine the data-aided
channel estimates, namely one-dimensional (1-D)/two-dimensional (2-D) moving
average and Wiener filtering. Finally, the MMSE criteria is used to obtain the
best combination results and an iterative process is proposed to progressively
refine the estimation. Both MSE and BER simulations using specifications of the
DTMB system are carried out to prove the effectiveness of the proposed
algorithm even in very harsh channel conditions such as in the single frequency
network (SFN) case
Positioning of High-speed Trains using 5G New Radio Synchronization Signals
We study positioning of high-speed trains in 5G new radio (NR) networks by
utilizing specific NR synchronization signals. The studies are based on
simulations with 3GPP-specified radio channel models including path loss,
shadowing and fast fading effects. The considered positioning approach exploits
measurement of Time-Of-Arrival (TOA) and Angle-Of-Departure (AOD), which are
estimated from beamformed NR synchronization signals. Based on the given
measurements and the assumed train movement model, the train position is
tracked by using an Extended Kalman Filter (EKF), which is able to handle the
non-linear relationship between the TOA and AOD measurements, and the estimated
train position parameters. It is shown that in the considered scenario the TOA
measurements are able to achieve better accuracy compared to the AOD
measurements. However, as shown by the results, the best tracking performance
is achieved, when both of the measurements are considered. In this case, a very
high, sub-meter, tracking accuracy can be achieved for most (>75%) of the
tracking time, thus achieving the positioning accuracy requirements envisioned
for the 5G NR. The pursued high-accuracy and high-availability positioning
technology is considered to be in a key role in several envisioned HST use
cases, such as mission-critical autonomous train systems.Comment: 6 pages, 5 figures, IEEE WCNC 2018 (Wireless Communications and
Networking Conference
Multibranch Autocorrelation Method for Doppler Estimation in Underwater Acoustic Channels
In underwater acoustic (UWA) communications, Doppler estimation is one of the major stages in a receiver. Two Doppler estimation methods are often used: the cross-ambiguity function (CAF) method and the single-branch autocorrelation (SBA) method. The former results in accurate estimation but with a high complexity, whereas the latter is less complicated but also less accurate. In this paper, we propose and investigate a multibranch autocorrelation (MBA) Doppler estimation method. The proposed method can be used in communication systems with periodically transmitted pilot signals or repetitive data transmission. For comparison of the Doppler estimation methods, we investigate an orthogonal frequency-division multiplexing (OFDM) communication system in multiple dynamic scenarios using the Waymark simulator, allowing virtual UWA signal transmission between moving transmitter and receiver. For the comparison, we also use the OFDM signals recorded in a sea trial. The comparison shows that the receiver with the proposed MBA Doppler estimation method outperforms the receiver with the SBA method and its detection performance is close to that of the receiver with the CAF method, but with a significantly lower complexity
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