32 research outputs found

    Circular Convolution Filter Bank Multicarrier (FBMC) System with Index Modulation

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    Orthogonal frequency division multiplexing with index modulation (OFDM-IM), which uses the subcarrier indices as a source of information, has attracted considerable interest recently. Motivated by the index modulation (IM) concept, we build a circular convolution filter bank multicarrier with index modulation (C-FBMC-IM) system in this paper. The advantages of the C-FBMC-IM system are investigated by comparing the interference power with the conventional C-FBMC system. As some subcarriers carry nothing but zeros, the minimum mean square error (MMSE) equalization bias power will be smaller comparing to the conventional C-FBMC system. As a result, our C-FBMC-IM system outperforms the conventional C-FBMC system. The simulation results demonstrate that both BER and spectral efficiency improvement can be achieved when we apply IM into the C-FBMC system

    Performance analysis and optimization of DCT-based multicarrier system on frequency-selective fading channels

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    Regarded as one of the most promising transmission techniques for future wireless communications, the discrete cosine transform (DCT) based multicarrier modulation (MCM) system employs cosine basis as orthogonal functions for real-modulated symbols multiplexing, by which the minimum orthogonal frequency spacing can be reduced by half compared to discrete Fourier transform (DFT) based one. With a time-reversed pre-filter employed at the front of the receiver, interference-free one-tap equalization is achievable for the DCT-based systems. However, due to the correlated pre-filtering operation in time domain, the signal-to-noise ratio (SNR) is enhanced as a result at the output. This leads to reformulated detection criterion to compensate for such filtering effect, rendering minimum-mean-square-error (MMSE) and maximum likelihood (ML) detections applicable to the DCT-based multicarrier system. In this paper, following on the pre-filtering based DCT-MCM model that build in the literature work, we extend the overall system by considering both transceiver perfections and imperfections, where frequency offset, time offset and insufficient guard sequence are included. In the presence of those imperfection errors, the DCT-MCM systems are analysed in terms of desired signal power, inter-carrier interference (ICI) and inter-symbol interference (ISI). Thereafter, new detection algorithms based on zero forcing (ZF) iterative results are proposed to mitigate the imperfection effect. Numerical results show that the theoretical analysis match the simulation results, and the proposed iterative detection algorithms are able to improve the overall system performance significantly

    Filter bank multicarrier waveforms for future wireless networks: interference analysis and cancellation

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    Billions of devices are expected to connect to future wireless networks. Although conventional orthogonal division multiplexing (OFDM) has proven to be an effective physical layer waveform for enhanced mobile broadband (eMBB), it experiences various challenges. For example, OFDM experiences high out-of-band (OOB) emission caused by the use of rectangular filters. This causes interference to adjacent frequency bands and make OFDM highly sensitive to asynchronous transmissions. Filter bank multicarrier (FBMC) systems have emerged as a promising waveform candidate to satisfy the requirements of future wireless networks. They employ prototype filters with faster spectral decay, which results in better OOB emission and spectral efficiency compared to OFDM. Also, FBMC systems support asynchronous transmissions, which can reduce the signaling overhead in future applications. However, in FBMC systems there is no subcarriers orthogonality, resulting in intrinsic interference. The purpose of this thesis is to address the intrinsic interference problem to make FBMC a viable option for practical application in future wireless networks. In this thesis, iterative interference cancellation (IIC) receivers are developed for FBMC systems to improve their performance and applicability in future applications. First, an IIC receiver is studied for uncoded FBMC with quadrature amplitude modulation (FBMC-QAM) systems. To improve the decoding performance, bit-interleaved coded modulation with iterative decoding (BICM-ID) is incorporated into the IIC receiver design and the technique of extrinsic information transfer (EXIT) chart analysis is used to track the convergence of the IIC-based BICM-ID receiver. Furthermore, the energy harvesting capabilities of FBMC is considered. Particularly, FBMC is integrated with a simultaneous wireless information and power transfer (SWIPT) technique. Finally, an interference cancellation receiver is investigated for asynchronous FBMC systems in both single and mixed numerology systems. Analytical expressions are derived for the various schemes and simulations results are shown to verify the performance of the different FBMC systems

    Review of Recent Trends

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    This work was partially supported by the European Regional Development Fund (FEDER), through the Regional Operational Programme of Centre (CENTRO 2020) of the Portugal 2020 framework, through projects SOCA (CENTRO-01-0145-FEDER-000010) and ORCIP (CENTRO-01-0145-FEDER-022141). Fernando P. Guiomar acknowledges a fellowship from “la Caixa” Foundation (ID100010434), code LCF/BQ/PR20/11770015. Houda Harkat acknowledges the financial support of the Programmatic Financing of the CTS R&D Unit (UIDP/00066/2020).MIMO-OFDM is a key technology and a strong candidate for 5G telecommunication systems. In the literature, there is no convenient survey study that rounds up all the necessary points to be investigated concerning such systems. The current deeper review paper inspects and interprets the state of the art and addresses several research axes related to MIMO-OFDM systems. Two topics have received special attention: MIMO waveforms and MIMO-OFDM channel estimation. The existing MIMO hardware and software innovations, in addition to the MIMO-OFDM equalization techniques, are discussed concisely. In the literature, only a few authors have discussed the MIMO channel estimation and modeling problems for a variety of MIMO systems. However, to the best of our knowledge, there has been until now no review paper specifically discussing the recent works concerning channel estimation and the equalization process for MIMO-OFDM systems. Hence, the current work focuses on analyzing the recently used algorithms in the field, which could be a rich reference for researchers. Moreover, some research perspectives are identified.publishersversionpublishe

    Code-Aided Channel Estimation in LDPC-Coded MIMO Systems

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    For a multiple-input multiple-output (MIMO) system with unknown channel state information (CSI), a novel low-density parity check (LDPC)-coded transmission (LCT) scheme with joint pilot and data channel estimation is proposed. To fine-tune the CSI, a method based on the constraints introduced by the coded data from an LDPC code is designed such that the MIMO detector exploits the fine-tuned CSI. For reducing the computational burden, a coordinate ascent algorithm is employed along with several approximation methods, effectively reducing the required times of MIMO detection and computational complexity to achieve a satisfying performance. Simulation results utilizing WiMAX standard LDPC codes and quadrature phase-shift keying (QPSK) modulation demonstrate gains of up to 1.3 dB at a frame error rate (FER) of 10410^{-4} compared to pilot-assisted transmission (PAT) over Rayleigh block-fading channels.Comment: This paper has been accepted by IEEE Wireless Communications Letter

    Multiple-Input Multiple-Output Detection Algorithms for Generalized Frequency Division Multiplexing

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    Since its invention, cellular communication has dramatically transformed personal lifes and the evolution of mobile networks is still ongoing. Evergrowing demand for higher data rates has driven development of 3G and 4G systems, but foreseen 5G requirements also address diverse characteristics such as low latency or massive connectivity. It is speculated that the 4G plain cyclic prefix (CP)-orthogonal frequency division multiplexing (OFDM) cannot sufficiently fulfill all requirements and hence alternative waveforms have been in-vestigated, where generalized frequency division multiplexing (GFDM) is one popular option. An important aspect for any modern wireless communication system is the application of multi-antenna, i.e. MIMO techiques, as MIMO can deliver gains in terms of capacity, reliability and connectivity. Due to its channel-independent orthogonality, CP-OFDM straightforwardly supports broadband MIMO techniques, as the resulting inter-antenna interference (IAI) can readily be resolved. In this regard, CP-OFDM is unique among multicarrier waveforms. Other waveforms suffer from additional inter-carrier interference (ICI), inter-symbol interference (ISI) or both. This possibly 3-dimensional interference renders an optimal MIMO detection much more complex. In this thesis, weinvestigate how GFDM can support an efficient multiple-input multiple-output (MIMO) operation given its 3-dimensional interference structure. To this end, we first connect the mathematical theory of time-frequency analysis (TFA) with multicarrier waveforms in general, leading to theoretical insights into GFDM. Second, we show that the detection problem can be seen as a detection problem on a large, banded linear model under Gaussian noise. Basing on this observation, we propose methods for applying both space-time code (STC) and spatial multiplexing techniques to GFDM. Subsequently, we propose methods to decode the transmitted signals and numerically and theoretically analyze their performance in terms of complexiy and achieved frame error rate (FER). After showing that GFDM modulation and linear demodulation is a direct application of Gabor expansion and transform, we apply results from TFA to explain singularities of the modulation matrix and derive low-complexity expressions for receiver filters. We derive two linear detection algorithms for STC encoded GFDM signals and we show that their performance is equal to OFDM. In the case of spatial multiplexing, we derive both non-iterative and iterative detection algorithms which base on successive interference cancellation (SIC) and minimum mean squared error (MMSE)-parallel interference cancellation (PIC) detection, respectively. By analyzing the error propagation of the SIC algorithm, we explain its significantly inferior performance compared to OFDM. Using feedback information from the channel decoder, we can eventually show that near-optimal GFDM detection can outperform an optimal OFDM detector by up to 3dB for high SNR regions. We conclude that GFDM, given the obtained results, is not a general-purpose replacement for CP-OFDM, due to higher complexity and varying performance. Instead, we can propose GFDM for scenarios with strong frequency-selectivity and stringent spectral and FER requirements

    Modelling, Dimensioning and Optimization of 5G Communication Networks, Resources and Services

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    This reprint aims to collect state-of-the-art research contributions that address challenges in the emerging 5G networks design, dimensioning and optimization. Designing, dimensioning and optimization of communication networks resources and services have been an inseparable part of telecom network development. The latter must convey a large volume of traffic, providing service to traffic streams with highly differentiated requirements in terms of bit-rate and service time, required quality of service and quality of experience parameters. Such a communication infrastructure presents many important challenges, such as the study of necessary multi-layer cooperation, new protocols, performance evaluation of different network parts, low layer network design, network management and security issues, and new technologies in general, which will be discussed in this book

    Distributed Source Coding Techniques for Lossless Compression of Hyperspectral Images

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    This paper deals with the application of distributed source coding (DSC) theory to remote sensing image compression. Although DSC exhibits a significant potential in many application fields, up till now the results obtained on real signals fall short of the theoretical bounds, and often impose additional system-level constraints. The objective of this paper is to assess the potential of DSC for lossless image compression carried out onboard a remote platform. We first provide a brief overview of DSC of correlated information sources. We then focus on onboard lossless image compression, and apply DSC techniques in order to reduce the complexity of the onboard encoder, at the expense of the decoder's, by exploiting the correlation of different bands of a hyperspectral dataset. Specifically, we propose two different compression schemes, one based on powerful binary error-correcting codes employed as source codes, and one based on simpler multilevel coset codes. The performance of both schemes is evaluated on a few AVIRIS scenes, and is compared with other state-of-the-art 2D and 3D coders. Both schemes turn out to achieve competitive compression performance, and one of them also has reduced complexity. Based on these results, we highlight the main issues that are still to be solved to further improve the performance of DSC-based remote sensing systems

    Improved Recursive Algorithms for V-BLAST to Reduce the Complexity and Save Memories

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    Improvements I-IV were proposed to reduce the computational complexity of the original recursive algorithm for vertical Bell Laboratories layered space-time architecture (VBLAST). The existing recursive algorithm with speed advantage and that with memory saving incorporate Improvements I-IV and only Improvements III-IV into the original algorithm, respectively. To the best of our knowledge, the algorithm with speed advantage and that with memory saving require the lowest complexity and the least memories, respectively, among the existing recursive V-BLAST algorithms. We propose Improvements V and VI to replace Improvements I and II, respectively. Instead of the lemma for inversion of partitioned matrix applied in Improvement I, Improvement V uses another lemma to speed up the matrix inversion step by the factor of 1.67. Then the formulas adopted in our Improvement V are applied to deduce Improvement VI, which includes the improved interference cancellation scheme with memory saving. In the existing algorithm with speed advantage, the proposed algorithm I with speed advantage replaces Improvement I with Improvement V, while the proposed algorithm II with both speed advantage and memory saving replaces Improvements I and II with Improvements V and VI, respectively. Both proposed algorithms speed up the existing algorithm with speed advantage by the factor of 1.3, while the proposed algorithm II achieves the speedup of 1.86 and saves about half memories, compared to the existing algorithm with memory saving
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