336 research outputs found

    Low-Complexity Iterative Detection for Orthogonal Time Frequency Space Modulation

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    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

    A Study on Efficient Receiver Design for UWA Communication System

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    Underwater Acoustic Channels are fast varying channel according to environmental conditions and exhibit strong random fluctuations in amplitude as well as phase due to reflection, refraction, and diffraction. Due to these highly space, time and frequency dependent channel characteristics, it is very difficult to establish reliable and long-range underwater acoustic communication. In this project, channel modeling has been done showing the different channel characteristics of underwater and their dependencies on frequency, temperature, pressure, salinity etc. Also, it has been shown through some theoretical and practical results that the nakagami fading is the best suitable generalized fading to be used in underwater. In this research work various techniques such as equalization, pilot based OFDM and LDPC Coding has also been done to mitigate the channel fading effect and to improve the performance. An adaptive equalizer has been implemented through three different algorithms LMS, NLMS and RLS for linear as well as non-linear channels to mitigate ISI and, their convergence characteristics along with bit error rate performance has been compared. Two types of pilot insertion, block and Comb type has also been done while implementing OFDM. Block type pilot based OFDM is suitable for slow fading and comb type pilot based OFDM is suitable for a fast fading channel. As in underwater, both types of fading exist, hence, lattice type pilot based OFDM is the best suitable for underwater acoustic communication. LDPC channel coding through which almost Shannon capacity performance can be achieved; has also been implemented taking nakagami channel fading. Bit error rate performance has been compared for different LDPC decoding techniques and for different code rate

    An Iterative Receiver for OFDM With Sparsity-Based Parametric Channel Estimation

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    In this work we design a receiver that iteratively passes soft information between the channel estimation and data decoding stages. The receiver incorporates sparsity-based parametric channel estimation. State-of-the-art sparsity-based iterative receivers simplify the channel estimation problem by restricting the multipath delays to a grid. Our receiver does not impose such a restriction. As a result it does not suffer from the leakage effect, which destroys sparsity. Communication at near capacity rates in high SNR requires a large modulation order. Due to the close proximity of modulation symbols in such systems, the grid-based approximation is of insufficient accuracy. We show numerically that a state-of-the-art iterative receiver with grid-based sparse channel estimation exhibits a bit-error-rate floor in the high SNR regime. On the contrary, our receiver performs very close to the perfect channel state information bound for all SNR values. We also demonstrate both theoretically and numerically that parametric channel estimation works well in dense channels, i.e., when the number of multipath components is large and each individual component cannot be resolved.Comment: Major revision, accepted for IEEE Transactions on Signal Processin

    A Proof of Concept for OTFS Resilience in Doubly-Selective Channels by GPU-Enabled Real-Time SDR

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    Orthogonal time frequency space (OTFS) is a modulation technique which is robust against the disruptive effects of doubly-selective channels. In this paper, we perform an experimental study of OTFS by a real-time software defined radio (SDR) setup. Our SDR consists of a Graphical Processing Unit (GPU) for signal processing programmed using Sionna and TensorFlow, and Universal Software Radio Peripheral (USRP) devices for air interface. We implement a low-latency transceiver structure for OTFS and investigate its performance under various Doppler values. By comparing the performance of OTFS with Orthogonal Frequency Division Multiplexing (OFDM), we demonstrate that OTFS is highly robust against the disruptive effects of doubly-selective channels in a real-time experimental setup.Comment: ACCEPTED for 2023 IEEE Global Communications Conference: Wireless Communication

    A Reduced Complexity Ungerboeck Receiver for Quantized Wideband Massive SC-MIMO

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    Employing low resolution analog-to-digital converters in massive multiple-input multiple-output (MIMO) has many advantages in terms of total power consumption, cost and feasibility of such systems. However, such advantages come together with significant challenges in channel estimation and data detection due to the severe quantization noise present. In this study, we propose a novel iterative receiver for quantized uplink single carrier MIMO (SC-MIMO) utilizing an efficient message passing algorithm based on the Bussgang decomposition and Ungerboeck factorization, which avoids the use of a complex whitening filter. A reduced state sequence estimator with bidirectional decision feedback is also derived, achieving remarkable complexity reduction compared to the existing receivers for quantized SC-MIMO in the literature, without any requirement on the sparsity of the transmission channel. Moreover, the linear minimum mean-square-error (LMMSE) channel estimator for SC-MIMO under frequency-selective channel, which do not require any cyclic-prefix overhead, is also derived. We observe that the proposed receiver has significant performance gains with respect to the existing receivers in the literature under imperfect channel state information.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl
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