224 research outputs found
Adaptive Blind MPSK Constellation Recovery and Equalization for Cognitive Radio Applications
Cognitive radio is considered a relevant communication paradigm to deal with the increasing demands in modern communications systems. Adaptive schemes are required to recognize channel conditions and to properly adjust main transmission parameters to improve the quality of communications. In this direction, blind algorithms to recover constellation, from phase-modulated signals, represent a means to implement cognitive capabilities to allow automatic modulation recognition (AMR) on receivers. Commonly, the most popular approaches for blind constellation recovery are based on a two-step scheme. The first step uses to equalize channel effects and reduce inter-symbol interference (ISI). The second step carries out constellation recovery utilizing phase locked loop (PLL) systems like the Costas Loop, then to classify the incoming signal. This work proposes a novel single-step blind adaptive filter solution, inspired by an adaptive interference canceler, for joint equalization and constellation symbol recovery from received phase shift keying (PSK) waveforms. Furthermore, we propose new coefficients update mechanisms based on the constant amplitude of PSK signals. The proposed solution exhibits reduced computational complexity compared to the state of the art and a reduced time of convergence. Additionally, the proposed scheme does not require a training sequence to operate properly. The obtained results clearly show that the proposed scheme significantly improves accuracy regarding phase symbol estimation and ISI reduction.This work has been partially funded by the Spanish National project
IRENE-EARTH (PID2020-115323RB-C33 / AEI / 10.13039/501100011033)
as well as by the Federal Ministry of Education and Research (BMBF,
Germany) within the 6G Research and Innovation Cluster 6G-RIC under Grant
16KISK020K.Publicad
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Digital Signal Processing for Coherent Transceivers Employing Multilevel Formats
Digital coherent transceivers have revolutionized optical fiber communications due to their superior performance offered compared to intensity modulation and direct detection based alternatives. As systems employing digital coherent transceivers seek to approach their information theoretic capacity, the use of multilevel modulation formats combined with appropriate forward error correction becomes essential. Given this context, in this tutorial paper, we therefore explore the digital signal processing (DSP) utilized in a coherent transceiver with a focus on multilevel modulation formats. By way of an introduction, we open by discussing the photonic technology required to realize a coherent transceiver. After discussing this interface between the analog optical channel and the digital domain, the rest of the paper is focused on DSP. We begin by discussing algorithms that correct for imperfections in the optical to digital conversion, including IQ imbalance and timing skew. Next, we discuss channel equalization including means for their realization for both quasi-static and dynamic channel impairments. Synchronization algorithms that correct for the difference between the transmitter and receiver oscillators both optical and electrical are then discussed and issues associated with symbol decoding highlighted. For most of the cases, we start with polarization division multiplexed quadrature phase-shift keying (PDM-QPSK) format as a basis and then discuss the extension to allow for high order multilevel formats. Finally, we conclude by discussing some of the open research challenges in the field.This work was supported in part by the EU project ICONE (608099) and EPSRC through INSIGHT (EP/L026155/2) and UNLOC (EP/J017582/1)
Channel estimation techniques for filter bank multicarrier based transceivers for next generation of wireless networks
A dissertation submitted to Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfillment of the requirements for the degree of Master of Science in Engineering (Electrical and Information Engineering), August 2017The fourth generation (4G) of wireless communication system is designed based on the principles of cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) where the cyclic prefix (CP) is used to combat inter-symbol interference (ISI) and inter-carrier interference (ICI) in order to achieve higher data rates in comparison to the previous generations of wireless networks. Various filter bank multicarrier systems have been considered as potential waveforms for the fast emerging next generation (xG) of wireless networks (especially the fifth generation (5G) networks). Some examples of the considered waveforms are orthogonal frequency division multiplexing with offset quadrature amplitude modulation based filter bank, universal filtered multicarrier (UFMC), bi-orthogonal frequency division multiplexing (BFDM) and generalized frequency division multiplexing (GFDM). In perfect reconstruction (PR) or near perfect reconstruction (NPR) filter bank designs, these aforementioned FBMC waveforms adopt the use of well-designed prototype filters (which are used for designing the synthesis and analysis filter banks) so as to either replace or minimize the CP usage of the 4G networks in order to provide higher spectral efficiencies for the overall increment in data rates. The accurate designing of the FIR low-pass prototype filter in NPR filter banks results in minimal signal distortions thus, making the analysis filter bank a time-reversed version of the corresponding synthesis filter bank. However, in non-perfect reconstruction (Non-PR) the analysis filter bank is not directly a time-reversed version of the corresponding synthesis filter bank as the prototype filter impulse response for this system is formulated (in this dissertation) by the introduction of randomly generated errors. Hence, aliasing and amplitude distortions are more prominent for Non-PR.
Channel estimation (CE) is used to predict the behaviour of the frequency selective channel and is usually adopted to ensure excellent reconstruction of the transmitted symbols. These techniques can be broadly classified as pilot based, semi-blind and blind channel estimation schemes. In this dissertation, two linear pilot based CE techniques namely the least square (LS) and linear minimum mean square error (LMMSE), and three adaptive channel estimation schemes namely least mean square (LMS), normalized least mean square (NLMS) and recursive least square (RLS) are presented, analyzed and documented. These are implemented while exploiting the near orthogonality properties of offset quadrature amplitude modulation (OQAM) to mitigate the effects of interference for two filter bank waveforms (i.e. OFDM/OQAM and GFDM/OQAM) for the next generation of wireless networks assuming conditions of both NPR and Non-PR in slow and fast frequency selective Rayleigh fading channel. Results obtained from the computer simulations carried out showed that the channel estimation schemes performed better in an NPR filter bank system as compared with Non-PR filter banks. The low performance of Non-PR system is due to the amplitude distortion and aliasing introduced from the random errors generated in the system that is used to design its prototype filters. It can be concluded that RLS, NLMS, LMS, LMMSE and LS channel estimation schemes offered the best normalized mean square error (NMSE) and bit error rate (BER) performances (in decreasing order) for both waveforms assuming both NPR and Non-PR filter banks.
Keywords: Channel estimation, Filter bank, OFDM/OQAM, GFDM/OQAM, NPR, Non-PR, 5G, Frequency selective channel.CK201
Compensation of fibre impairments in coherent optical systems
Tese de mestrado integrado. Engenharia ElectrotΓ©cnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 201
Dsp Implementation of channel estimation algorithms for OFDM systems
The channel estimation based on the block - type, comb-type and lattice-type structure is studied. The Block type pilot structure is performed on every block of OFDM symbols and the Comb type pilot arrangement is performed on every OFDM symbol. Which are inserted particular data intervals. Comb-type and block type spectrums are verified and the bit error rate is compared. The objective of this thesis is to implementation channel estimation algorithm OFDM system implementation of the C6713 Digital Signal Processor (DSP) of Texas Instruments (TI). First, the basic channel LS and MMSE channel estimation techniques implemented and LMS, NLMS and RLS were implemented and tested using Simulink Next this model is an implementation on DSP C6713. Finally a comparison of the implemented estimator and compared BER values and mean square error estimated in LMS NLMS and RLS algorithms performed
Multiuser MIMO-OFDM for Next-Generation Wireless Systems
This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base stationβs or radio portβs coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems
Optics for AI and AI for Optics
Artificial intelligence is deeply involved in our daily lives via reinforcing the digital transformation of modern economies and infrastructure. It relies on powerful computing clusters, which face bottlenecks of power consumption for both data transmission and intensive computing. Meanwhile, optics (especially optical communications, which underpin todayβs telecommunications) is penetrating short-reach connections down to the chip level, thus meeting with AI technology and creating numerous opportunities. This book is about the marriage of optics and AI and how each part can benefit from the other. Optics facilitates on-chip neural networks based on fast optical computing and energy-efficient interconnects and communications. On the other hand, AI enables efficient tools to address the challenges of todayβs optical communication networks, which behave in an increasingly complex manner. The book collects contributions from pioneering researchers from both academy and industry to discuss the challenges and solutions in each of the respective fields
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