Elsevier

Physical Communication

Volume 25, Part 2, December 2017, Pages 348-354
Physical Communication

Full length article
Multi-level quantization and blind equalization based direct transmission method of digital baseband signal

https://doi.org/10.1016/j.phycom.2017.04.008Get rights and content

Abstract

The direct transmission of digital baseband signals has practical significance in the field of Ethernet terminal connection, high-speed digital communication, data transmission of various types of information peripherals. The signal amplitude gradually decays while the transmission distance increases. Also the attenuation is proportional to the signal frequency, resulting in signal distortion and receiving error. It is a common method for digital baseband signal transmission to use pre-emphasis chip and equalizer chip to improve the transmission quality with a wide range of mature applications. This paper describes a new type of digital signal transmission method, as the receiver using analog-to-digital converter, instead of equalizer chip, to achieve the multi-level quantization of receiving time-domain data waveform. The waveform of the transmitted digital high and low level signal is sampled into multi-bit values. Then, the paper realizes adaptive frequency domain equalization based on soft threshold and makes use of multi-level quantization soft information for error correction. Error correcting code is mainly used to correct the error caused by the channel bandwidth limit, external noise or interference in the process of data transmission, so as to improve the stability and reliability of the transmission. The paper uses the two-stage error correcting codec system based on both Turbo and BCH coding, to achieve the high performance of Turbo code, and good characters of respond time and complexity. The transmitter outputs 12.5 MHz pseudo-random sequence through a 199.93 meter unshielded balanced twisted pair transmission medium. And the receiver circuit using a 62.5MSPS analog-to-digital converter over-samples the waveform to 8-level quantity. The output error of a 65536 bit pseudo-random sequence is less than 8 bits, and the error correction can be further improved by 8b-10b codec. Compared with the traditional pre-emphasis and balanced interface ICs connection, the method described in this article has the advantages of longer transmission distance, better flexibility and wider scope of use.

Introduction

Mobile communication technology and optical fiber communication technology are quite popular and important communication research topics in recent years  [1], [2]. However, the digital baseband signal transmission by wired communication is still an important tool and technology, widely used in the computer high-speed terminal communication, Ethernet terminal connection, industrial control data-bus and other fields. Many of the channel coding and decoding techniques of mobile communication cannot be directly applied to the direct transmission of digital baseband signals (DTDBS)  [3]. The traditional connection method of DTDBS is using interface chips to achieve the signal driving and pre-emphasis before transmission, and using equalizer chips to achieve signal waveform shaping and information extraction at data receiving terminal. In recent years, the rapid development and application of high-speed analog-to-digital converter devices provide the technical possibility for direct transmission of soft threshold baseband signals based on multi-level quantization. Turbo channel codec  [4] and equalization  [5], [6], [7], [8] are one of the important technological improvement of channel codec and signal transmission in the past two decades, and have been applied in many fields. The adaptive equalization method can be more flexible than the fixed equalizer interface chips to adapt to different transmission environments, especially in the variable environment  [9]. In this paper, a soft-threshold digital baseband signal direct transmission system based on high-speed analog-to-digital converter and minimum mean square adaptive equalization is presented. The actual circuit experiments and computer simulation output are carried out to verify the feasibility of the related method.

Section snippets

Digital baseband signal direct transmission system

The transmission system is shown in Fig. 1 below. The transmitter outputs digital data bits directly. The low electrical level means “0” and the high level is “1”, as shown in point A in Fig. 1. After long-distance unshielded copper uniform twisted pair transmission, the quality of signal waves disgraced by distortion, transmission media bandwidth limit, signal attenuation, crosstalk and other reasons. And it will lead to the instability of amplitudes and edges, even several parts of the data

Multi-level quantization of digital baseband signal

The classical digital signal direct transmission system normally uses the general or custom equalizer chip to carry on the hard threshold judgment and the shaping to the signal waveform. This paper uses a different design method. First of all, the high-speed analog-to-digital converter was used to over-sampling signal waveform on receiver side. And digital signal time domain waveform after the wire transmission (including strong distortion and interference) was sampled into multi-bit binary

Adaptive equalization of digital baseband signal direct transmission

In this paper, the adaptive equalizer in the system uses the least squares (LMS) adaptive algorithm implemented in the FPGA to realize the frequency domain equalization and soft threshold decision of the signal waveform. The main function of the equalizer is to compensate for the non-ideal response characteristics of the wired channel, eliminating the inter-symbol interference of the received signal. The frequency domain response characteristics of the transmission channel are mainly related to

Realization of the digital baseband signal direct transmission system

Fig. 6 shows the actual system designed in this paper. The signal source generates a 12.5 MHz pseudo-random digital baseband sequence at the LVDS level through the FPGA and outputs directly to the unshielded copper twisted pair. The receiving end realizes the 8-bit 256-level quantization of the receiver’s time domain signal waveform through the 62.5MSPS high-speed analog-to-digital conversion circuit. FPGA-based Adaptive Soft Threshold Equalizer Realizes Quasi-Real-Time Data Sequence Output by

Discussion

This paper describes a long-distance digital baseband signal transmission system, based on time domain oversampling, multi-level quantization and soft-threshold adaptive equalization. This method oversamples the signal waveform at the channel terminal by a high-speed analog-to-digital converter, which realizes multi-level quantization and provides a large amount of information for the soft-threshold iterative equalization and error correction. In the circuit experiment conducted in the

Acknowledgments

This work was supported in part by Tianjin Edge Technology and Applied Basic Research Project (14JCYBJC15800) in China, in part by the National Natural Science Foundations of China under Grant No. 61501319, in part by the TianJin Natural Science Foundations of China, in part by the open project (MOMST2015-7) of Key Laboratory of Micro Opto-electro Mechanical System Technology, Tianjin University, Ministry of Education, in part by the Photoelectric Information and Instrument–Engineering Research

Maolin Ji was born in Tianjin in 1985. He received the M.S. degrees from College of Precision Instrument and Opto-electronics Engineering, Tianjin University, in 2010.

Since 2015, he has been an engineer in Deviser, Tianjin. Nowadays, he also has been with the Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University. His research interests include next generation wireless mobile communication, digital baseband signal processing.

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Maolin Ji was born in Tianjin in 1985. He received the M.S. degrees from College of Precision Instrument and Opto-electronics Engineering, Tianjin University, in 2010.

Since 2015, he has been an engineer in Deviser, Tianjin. Nowadays, he also has been with the Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University. His research interests include next generation wireless mobile communication, digital baseband signal processing.

Jin Chen was born in Wuhu, China, in 1976. He received the M.S. degree from Tianjin Normal University and the Ph.D. degree from College of Precision Instrument and Opto-electronics Engineering, Tianjin University, in 2002 and 2013 respectively.

Since 2005, He has been working in Tianjin Normal University. He is an associate professor of Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission. His research interests include acoustic and opto-electronic signal acquisition and processing, broadband signal processing.

Zeng Liu was born in Zaozhuang, China, in 1990. He received the B.S. degree from Shandong Jiaotong College in 2014. He is currently working toward the M.S. degree of Tianjin Normal University.

His research interests include digital database signal transmission and signal processing.

Ying Tong was born in Tianjin, China, in 1982. She received the M.S. degree in educational technology from Tianjin Normal University and the Ph.D. degree from Tianjin University in 2004 and 2015 respectively.

Since 2004, she has been working in Tianjin Normal University. She is a lecturer of Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission. Her research interests include computer vision detection and digital image processing.

Fajie Duan was born in HuNan, China, in 1968. He received the M.S. degrees from TianJin University and the Ph.D. degree from TianJin University (State Key Lab of Precision Measuring Technology and Instruments), TianJin, China, in 1991 and 1994, respectively.

He worked as a professor at TianJin University (State Key Lab of Precision Measuring Technology and Instruments) since 1994.

His research interest focuses on the design of the array system, array signal processing, acoustic detection of marine, measurement technology, optical fiber sensing technology and so on. He has won one National Scientific and Technological Progress Second Prize, one Provincial and Ministerial Level Scientific and Technological Progress Second Prize, one Provincial Natural Science prize, two Provincial and Ministerial Level Scientific and Technological Progress Third Prizes and one National Teaching Achievement Second Award. He was named the National New Century Excellent Talents of Ministry of Education in 2005. He is the author or coauthor of over 120 papers and holds seven patents.

Tariq S. Durrani (OBE FRSE FREng FIEEE FIET) is Research Professor of University of Strathclyde in the United Kingdom. He was University Deputy Principal (2000–2006) with major responsibility for University-wide strategic developments in Computing/Information Technology Infra-structure, Entrepreneurship, Staff Development and Lifelong Learning. He joined Strathclyde as a Lecturer in 1976, was made Professor in 1982; Department Head (1990–1994) of one of the largest UK EEE Departments. He was Chair, Institute for Communications and Signal Processing (2006–2007), and Head, Centre of excellence in Signal and Image Processing (2008–2009). Currently he is Research Professor in Electronic and Electrical Engineering at Strathclyde.

He has been Vice President (Natural Sciences 2007–2010, International 2012–2013) of the Royal Society of Edinburgh; Council (Board) Member, Scottish Funding Council. He was Director of the UK Government DTI Centre for Parallel Signal Processing (1989–1991), and the UK Research Council/DTI Scottish Transputer Centre (1991–1995) at Strathclyde. He has held several Directorships in key organizations—public/private, national/international. His research interests include communications, signal processing, technology management, higher education management. He has authored six books, and over 350 publications. He has supervised over forty Ph.D. theses.

Jiajia Jiang was born in TianMen, China, in 1986. He received the B.S. degrees from HeBei Normal University and the M.S. degree from TianJin University and the Ph.D. degree from TianJin University (State Key Lab of Precision Measuring Technology and Instruments), TianJin, China, in 2009 and 2014, respectively.

He worked as an assistant professor at TianJin University (State Key Lab of Precision Measuring Technology and Instruments) since 2014.

His research interest focuses on the design of the array system design and array signal processing. He is the author or coauthor of over 30 papers and holds ten patents.

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