2,920 research outputs found
Robust frequency-domain turbo equalization for multiple-input multiple-output (MIMO) wireless communications
This dissertation investigates single carrier frequency-domain equalization (SC-FDE) with multiple-input multiple-output (MIMO) channels for radio frequency (RF) and underwater acoustic (UWA) wireless communications. It consists of five papers, selected from a total of 13 publications. Each paper focuses on a specific technical challenge of the SC-FDE MIMO system. The first paper proposes an improved frequency-domain channel estimation method based on interpolation to track fast time-varying fading channels using a small amount of training symbols in a large data block. The second paper addresses the carrier frequency offset (CFO) problem using a new group-wise phase estimation and compensation algorithm to combat phase distortion caused by CFOs, rather than to explicitly estimate the CFOs. The third paper incorporates layered frequency-domain equalization with the phase correction algorithm to combat the fast phase rotation in coherent communications. In the fourth paper, the frequency-domain equalization combined with the turbo principle and soft successive interference cancelation (SSIC) is proposed to further improve the bit error rate (BER) performance of UWA communications. In the fifth paper, a bandwidth-efficient SC-FDE scheme incorporating decision-directed channel estimation is proposed for UWA MIMO communication systems. The proposed algorithms are tested by extensive computer simulations and real ocean experiment data. The results demonstrate significant performance improvements in four aspects: improved channel tracking, reduced BER, reduced computational complexity, and enhanced data efficiency --Abstract, page iv
Frequency-domain transmit processing for MIMO SC-FDMA in wideband propagation channels
This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available
Frequency Spreading Equalization in Multicarrier Massive MIMO
Application of filter bank multicarrier (FBMC) as an effective method for
signaling over massive MIMO channels has been recently proposed. This paper
further expands the application of FBMC to massive MIMO by applying frequency
spreading equalization (FSE) to these channels. FSE allows us to achieve a more
accurate equalization. Hence, higher number of bits per symbol can be
transmitted and the bandwidth of each subcarrier can be widened. Widening the
bandwidth of each subcarrier leads to (i) higher bandwidth efficiency; (ii)
lower complexity; (iii) lower sensitivity to carrier frequency offset (CFO);
(iv) reduced peak-to-average power ratio (PAPR); and (iv) reduced latency. All
these appealing advantages have a direct impact on the digital as well as
analog circuitry that is needed for the system implementation. In this paper,
we develop the mathematical formulation of the minimum mean square error (MMSE)
FSE for massive MIMO systems. This analysis guides us to decide on the number
of subcarriers that will be sufficient for practical channel models.Comment: Accepted in IEEE ICC 2015 - Workshop on 5G & Beyond - Enabling
Technologies and Application
Robust massive MIMO Equilization for mmWave systems with low resolution ADCs
Leveraging the available millimeter wave spectrum will be important for 5G.
In this work, we investigate the performance of digital beamforming with low
resolution ADCs based on link level simulations including channel estimation,
MIMO equalization and channel decoding. We consider the recently agreed 3GPP NR
type 1 OFDM reference signals. The comparison shows sequential DCD outperforms
MMSE-based MIMO equalization both in terms of detection performance and
complexity. We also show that the DCD based algorithm is more robust to channel
estimation errors. In contrast to the common believe we also show that the
complexity of MMSE equalization for a massive MIMO system is not dominated by
the matrix inversion but by the computation of the Gram matrix.Comment: submitted to WCNC 2018 Workshop
- âŠ