scholarly journals Transceiver Design for GFDM with Hexagonal Time–Frequency Allocation Using the Polyphase Decomposition

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1862
Author(s):  
Evren Catak ◽  
Arild Moldsvor ◽  
Mohammad Derawi
Keyword(s):  
Energy Consumption ◽  
Computational Complexity ◽  
Communication Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Channel Model ◽  
Low Latency ◽  
Frequency Division Multiplexing ◽  
Frequency Division ◽  
Next Generation ◽  
Time Frequency

Generalized frequency division multiplexing (GFDM) is a waveform for the next-generation communication systems to succeed in the drawbacks of orthogonal frequency division multiplexing (OFDM). The symbols of users are transmitted with the time- and frequency-shifted versions of a prototype filter. According to filtering operation, the computational complexity and processing load are high for the devices that suffer from energy consumption. The communication systems are required to support the new generation devices that need low energy consumption and low latency issues. Motivated by such demands of the next-generation communication system, we propose a novel GFDM waveform that we call hexagonal GFDM. The contributions of the hexagonal GFDM are that it: (i) supports short transmission time based on its hexagonal time–frequency allocations; and (ii) provides low latency communication with low computational complexity manner. Furthermore, we design a transmitter and receiver structure in a less complicated way with mathematical derivation by using polyphase decomposition and Fourier transform (FT) transformation. The proposed systems are realized analytically and investigated over Rayleigh fading channel model through computer simulations.

scholarly journals Sparse code multiple access on the generalized frequency division multiplexing

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Guilherme P. Aquino ◽  
Luciano L. Mendes
Keyword(s):  
Communication Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Access ◽  
Physical Layer ◽  
Spectrum Efficiency ◽  
Sparse Code ◽  
Frequency Division Multiplexing ◽  
Frequency Division ◽  
Time Frequency ◽  
Performance Loss

Abstract Recent advances in the communication systems culminated in a new class of multiple access schemes, named non-orthogonal multiple access (NOMA), where the main goal is to increase the spectrum efficiency by overlapping data from different users in a single time-frequency resource used by the physical layer. NOMA receivers can resolve the interference among data symbols from different users, increasing the overall system spectrum efficiency without introducing symbol error rate (SER) performance loss, which makes this class of multiple access techniques interesting for future mobile communication systems. This paper analyzes one promising NOMA technique, called sparse code multiple access (SCMA), where C users can share U<C time-frequency resources from the physical layer. Initially, the SCMA and orthogonal frequency division multiplexing (OFDM) integration is considered, defining a benchmark for the overall SER performance for the multiple access technique. Furthermore, this paper proposes the SCMA and generalized frequency division multiplexing (GFDM) integration. Since GFDM is a highly flexible non-orthogonal waveform that can mimic several other waveforms as corner cases, it is an interesting candidate for future wireless communication systems. This paper proposes two approaches for combining SCMA and GFDM. The first one combines a soft equalizer, called block expectation propagation (BEP), and a multi-user detection (MUD) scheme based on the sum-product algorithm (SPA). This approach achieves the best SER performance, but with the significant increment of the complexity at the receiver. In the second approach, BEP is integrated with a simplified MUD, which is an original contribution of this paper, aiming for reducing the receiver’s complexity at the cost of SER performance loss. The solutions proposed in this paper show that SCMA-GFDM can be an interesting solution for future mobile networks.

scholarly journals Performance Analysis of OFDMA vs. NOMA in Cognitive Radio Network

2021 ◽  
Vol 9 (VI) ◽  
pp. 2483-2488
Author(s):  
E. Alwin Richard
Keyword(s):  
Communication Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Access ◽  
Spectrum Efficiency ◽  
Frequency Division Multiplexing ◽  
Frequency Division ◽  
Time Frequency ◽  
New Class ◽  
Overlapping Data ◽  
Multiple Access Schemes

Recent advancements in communication systems have resulted in a new class of multiple access schemes known as non-orthogonal multiple access (NOMA), the primary goal of which is to increase spectrum efficiency by overlapping data from different users in a single time-frequency resource used by the physical layer. NOMA receivers can resolve interference between data symbols from various users, hence increasing throughput. Initially, the combination of SCMA and orthogonal frequency division multiplexing (OFDM) is addressed, establishing a baseline for the overall SER performance of the multiple access strategy. Furthermore, this work suggests the merging of SCMA with generalised frequency division multiplexing (GFDM).GFDM is an intriguing possibility for future wireless communication systems since it is a very flexible non-orthogonal waveform that can imitate various different waveforms as corner cases. This research suggests two methods for integrating SCMA with GFDM.

scholarly journals Pilot Placement Schemes for Channel Estimation of Proposed 5G-GFDM System

2019 ◽  
Vol 27 ◽  
pp. 01001
Author(s):  
Suleman Tahir ◽  
Shahzad Amin Sheikh ◽  
Omer Bin Saeed
Keyword(s):  
Channel Estimation ◽  
Communication Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Frequency Division Multiplexing ◽  
Frequency Division ◽  
Next Generation ◽  
High Data ◽  
Pilot Symbols ◽  
Data Rates ◽  
A New Technique

Orthogonal Frequency Division Multiplexing (OFDM) is a highly regarded technique used in the 4G mobile communication systems to provide reliable communication and high data rates due to the orthogonality between its sub carriers. However, it cannot be used in the next generation cellular system i.e. 5G. Thus, a new technique Generalized Frequency Division Multiplexing (GFDM) has been proposed to meet the demands of the next generation systems, which are higher data rates than 4G, minimum response time, lower power consumption etc. GFDM is a non-orthogonal, multicarrier scheme, which seems to fulfil the requirements of the new wireless communication system. The aim of this paper is to use the pilot symbols and their optimum placements within the data for the channel estimation of the GFDM system. It is shown that the optimum arrangement of the pilot symbols is to place them uniformly on equal intervals within the data and to cluster them in the middle of the data.

scholarly journals EVM Loss: A Loss Function for Training Neural Networks in Communication Systems

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1094
Author(s):  
Scott Stainton ◽  
Martin Johnston ◽  
Satnam Dlay ◽  
Paul Anthony Haigh
Keyword(s):  
Neural Networks ◽  
Loss Function ◽  
Communication Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Frequency Division Multiplexing ◽  
Efficiency Gain ◽  
Frequency Division ◽  
Error Vector Magnitude ◽  
Modulation Formats ◽  
Complex Approach

Neural networks and their application in communication systems are receiving growing attention from both academia and industry. The authors note that there is a disconnect between the typical objective functions of these neural networks with regards to the context in which the neural network will eventually be deployed and evaluated. To this end, a new loss function is proposed and shown to increase the performance of neural networks when implemented in a communication system compared to previous methods. It is further shown that a ‘split complex’ approach used by many implementations can be improved via formalisation of the ‘concatenated complex’ approach described herein. Experimental results using the orthogonal frequency division multiplexing (OFDM) and spectrally efficient frequency division multiplexing (SEFDM) modulation formats with varying bandwidth compression factors over a wireless visible light communication (VLC) link validate the efficacy of the proposed method in a real system, achieving the lowest error vector magnitude (EVM), and thus bit error rate (BER), across all experiments, with a 5 dB to 10 dB improvement in the received symbols EVM overall compared to the baseline implementation, with bandwidth compressions down to 40% compared to OFDM, resulting in a spectral efficiency gain of 67%.

scholarly journals Channel estimation of OFDM in C-band communication systems under different distribution conditions

2021 ◽  
Vol 23 (3) ◽  
pp. 1778
Author(s):  
Heba Abdul-Jaleel Al-Asady ◽  
Hassan Falah Fakhruldeen ◽  
Mustafa Qahtan Alsudani
Keyword(s):  
Fourier Transform ◽  
Channel Estimation ◽  
Fast Fourier Transform ◽  
Communication Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Frequency Division Multiplexing ◽  
Frequency Division ◽  
Ofdm System ◽  
High Data ◽  
High Efficient

<p>Orthogonal frequency division multiplexing (OFDM) is a transmission system that uses multiple orthogonal carriers that are sent out at the same time. OFDM is a technique for mobile and wireless communication that has high-efficient frequency utilization, high data-rate transmission, simple and efficient implementation using the fast Fourier transform (FFT) and the inverse fast Fourier transform (IFFT), and reduces inter symbol interference (ISI) by inserting cyclic prefix (CP). One of the most important approaches in an OFDM system is channel estimation. In this paper, the orthogonal frequency division multiplexing system with the Rayleigh channel module is analyzed for different areas. The proposed approach used large numbers of subcarriers to transmit the signals over 64-QAM modulation with pilot add channel estimation. The accuracy of the OFDM system is shown in the measuring of the relationships of peak power to the noise ratio and bit error rate.</p>

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