A low-complexity security technique in physical layer for fixed LiFi communication systems

2020 ◽  
Vol 53 ◽  
pp. 102514
Author(s):  
Imene Romdhane ◽  
Heba Yuksel
Keyword(s):  
Communication Systems ◽  
Low Complexity ◽  
Physical Layer

scholarly journals Low-complexity beam-domain channel estimation and power allocation in hybrid architecture massive MIMO systems

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Xiao Chen ◽  
Zaichen Zhang ◽  
Liang Wu ◽  
Jian Dang
Keyword(s):  
Channel Estimation ◽  
Power Allocation ◽  
Spectral Efficiency ◽  
Communication Systems ◽  
Mimo Systems ◽  
Beam Steering ◽  
Estimation Method ◽  
Low Complexity ◽  
Estimation Accuracy ◽  
Hybrid Architecture

Abstract In this journal, we investigate the beam-domain channel estimation and power allocation in hybrid architecture massive multiple-input and multiple-output (MIMO) communication systems. First, we propose a low-complexity channel estimation method, which utilizes the beam steering vectors achieved from the direction-of-arrival (DOA) estimation and beam gains estimated by low-overhead pilots. Based on the estimated beam information, a purely analog precoding strategy is also designed. Then, the optimal power allocation among multiple beams is derived to maximize spectral efficiency. Finally, simulation results show that the proposed schemes can achieve high channel estimation accuracy and spectral efficiency.

scholarly journals Physical-Layer Security Improvement with Reconfigurable Intelligent Surfaces for 6G Wireless Communication Systems

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1439
Author(s):  
Janghyuk Youn ◽  
Woong Son ◽  
Bang Chul Jung
Keyword(s):  
Wireless Communication ◽  
Physical Layer Security ◽  
Communication Systems ◽  
Low Cost ◽  
Physical Layer ◽  
Base Station ◽  
Wireless Communication Systems ◽  
Secrecy Rate ◽  
Pilot Signal ◽  
Time Division

Recently, reconfigurable intelligent surfaces (RISs) have received much interest from both academia and industry due to their flexibility and cost-effectiveness in adjusting the phase and amplitude of wireless signals with low-cost passive reflecting elements. In particular, many RIS-aided techniques have been proposed to improve both data rate and energy efficiency for 6G wireless communication systems. In this paper, we propose a novel RIS-based channel randomization (RCR) technique for improving physical-layer security (PLS) for a time-division duplex (TDD) downlink cellular wire-tap network which consists of a single base station (BS) with multiple antennas, multiple legitimate pieces of user equipment (UE), multiple eavesdroppers (EVEs), and multiple RISs. We assume that only a line-of-sight (LOS) channel exists among the BS, the RISs, and the UE due to propagation characteristics of tera-hertz (THz) spectrum bands that may be used in 6G wireless communication systems. In the proposed technique, each RIS first pseudo-randomly generates multiple reflection matrices and utilizes them for both pilot signal duration (PSD) in uplink and data transmission duration (DTD) in downlink. Then, the BS estimates wireless channels of UE with reflection matrices of all RISs and selects the UE that has the best secrecy rate for each reflection matrix generated. It is shown herein that the proposed technique outperforms the conventional techniques in terms of achievable secrecy rates.

scholarly journals Multi-Domain Communication Systems and Networks: A Tensor-Based Approach

Network ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 50-74
Author(s):  
Divyanshu Pandey ◽  
Adithya Venugopal ◽  
Harry Leib
Keyword(s):  
Communication Systems ◽  
Physical Layer ◽  
Mathematical Framework ◽  
Trade Off ◽  
Information Theoretic ◽  
Time Frequency ◽  
Tensor Formulation ◽  
Processing Techniques ◽  
Multiple Domains ◽  
Signal Processing Techniques

Most modern communication systems, such as those intended for deployment in IoT applications or 5G and beyond networks, utilize multiple domains for transmission and reception at the physical layer. Depending on the application, these domains can include space, time, frequency, users, code sequences, and transmission media, to name a few. As such, the design criteria of future communication systems must be cognizant of the opportunities and the challenges that exist in exploiting the multi-domain nature of the signals and systems involved for information transmission. Focussing on the Physical Layer, this paper presents a novel mathematical framework using tensors, to represent, design, and analyze multi-domain systems. Various domains can be integrated into the transceiver design scheme using tensors. Tools from multi-linear algebra can be used to develop simultaneous signal processing techniques across all the domains. In particular, we present tensor partial response signaling (TPRS) which allows the introduction of controlled interference within elements of a domain and also across domains. We develop the TPRS system using the tensor contracted convolution to generate a multi-domain signal with desired spectral and cross-spectral properties across domains. In addition, by studying the information theoretic properties of the multi-domain tensor channel, we present the trade-off between different domains that can be harnessed using this framework. Numerical examples for capacity and mean square error are presented to highlight the domain trade-off revealed by the tensor formulation. Furthermore, an application of the tensor framework to MIMO Generalized Frequency Division Multiplexing (GFDM) is also presented.

scholarly journals Implementation of conventional communication system in deep learning

2017 ◽  
Vol 7 (1.1) ◽  
pp. 696
Author(s):  
Satyanarayana P ◽  
Charishma Devi. V ◽  
Sowjanya P ◽  
Satish Babu ◽  
N Syam Kumar ◽  
...  
Keyword(s):  
Machine Learning ◽  
Computer Vision ◽  
Communication Network ◽  
Deep Learning ◽  
Communication System ◽  
Communication Systems ◽  
Physical Layer ◽  
Learning Capacity ◽  
Constrained Learning ◽  
Complex Channel

Machine learning (ML) has been broadly connected to the upper layers of communication systems for different purposes, for example, arrangement of cognitive radio and communication network. Nevertheless, its application to the physical layer is hindered by complex channel conditions and constrained learning capacity of regular ML algorithms. Deep learning (DL) has been as of late connected for some fields, for example, computer vision and normal dialect preparing, given its expressive limit and advantageous enhancement ability. This paper describes about a novel use of DL for the physical layer. By deciphering a communication system as an auto encoder, we build up an essential better approach to consider communication system outline as a conclusion to-end reproduction undertaking that tries to together enhance transmitter and receiver in a solitary procedure. This DL based technique demonstrates promising execution change than traditional communication system.  

Joint low-complexity equalization and CFO estimation and compensation for UWA-OFDM communication systems

2020 ◽  
Vol 33 (3) ◽  
pp. e3972 ◽  
Author(s):  
Khaled Ramadan ◽  
Khalil F. Ramadan ◽  
Ahmed S. Fiky ◽  
Hasna Alam ◽  
Moawad I. Dessouky ◽  
...  
Keyword(s):  
Communication Systems ◽  
Low Complexity

scholarly journals Joint low-complexity equalisation and CFO compensation for DCT–OFDM communication systems based on SIC

2020 ◽  
Vol 14 (20) ◽  
pp. 3549-3559
Author(s):  
Khaled Ramadan ◽  
Moawad I. Dessouky ◽  
Fathi E. Abd El-Samie
Keyword(s):  
Communication Systems ◽  
Low Complexity ◽  
Cfo Compensation

scholarly journals A low complexity digital frequency calibration with high jitter immunity for ultra-low-power oscillators

2019 ◽  
Vol 17 ◽  
pp. 145-150
Author(s):  
Markus Scholl ◽  
Ralf Wunderlich ◽  
Stefan Heinen
Keyword(s):  
Low Power ◽  
Communication Systems ◽  
Calibration Method ◽  
Low Complexity ◽  
Frequency Stability ◽  
Wireless Communication Systems ◽  
Ultra Low Power ◽  
Wireless Transceiver ◽  
Digital Frequency ◽  
Frequency Calibration

Abstract. This paper presents a highly efficient digital frequency calibration method for ultra-low-power oscillators in wireless communication systems. This calibration method locks the ultra-low-power oscillator's output frequency to the reference clock of the wireless transceiver during its send- and receive-state to achieve frequency stability over process variation and temperature drifts. The introduced calibration scheme offers high jitter immunity and short locking periods overcoming frequency calibration errors for typical ultra-low-power oscillator's by utilizing non-linear segmented feedback levels. In measurements the proposed calibration method improves the frequency stability of an ultra-low-power 32 kHz oscillator from 53 to 10 ppm ∘C−1 over a wide temperature range for temperature drifts of less than 1 ∘C s−1 with an estimated power consumption of 185 nW while coping with relocking periods of 7 ms.

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