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DSP based receiver implementation for OFDM acoustic modems

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Abstract

Significant progress has been made recently on the use of multicarrier modulation in the form of orthogonal frequency division multiplexing (OFDM) for high data rate underwater acoustic communications. In this paper, we present implementation results of OFDM acoustic modems under different settings with either one or two parallel data streams transmitted, whose data rate is 3.2 KB/s or 6.4 KB/s, respectively, with QPSK modulation, rate-1/2 channel coding, and signal bandwidth of 6 kHz. To achieve real time operation, the processing time for each OFDM block shall be (much) less than the block duration of 210 ms. We first implement the receiver algorithms on a floating point TMS320C6713 DSP development board, running at 225 MHz. With convolutional coding, the per-block processing time is about 38 ms and 77 ms for single-input single-output (SISO) and multi-input multi-output (MIMO) settings, respectively, where there are two transmitters and two receivers in the latter case. With nonbinary low-density parity-check (LDPC) coding, which gains about 2 dB in error performance relative to convolutional coding, the per-block processing time increases to 50 ms and 101 ms for SISO and MIMO settings, respectively. We have also implemented the receiver algorithms using a fixed-point TMS320C6416 DSP development board, where the DSP core runs at 1 GHz. The per-block processing time reduces by two thirds with negligible performance degradation.

Introduction

There has been a growing interest in building distributed and scalable underwater wireless sensor networks (UWSN) that will bring significant advantages and benefits to a wide spectrum of underwater applications, such as ocean observation for scientific exploration, commercial exploitation, coastline protection and target detection in military events [1], [2], [3]. Providing high performance and reliable underwater acoustic communications at the physical layer is one of the fundamental issues for building UWSNs.

Among various modulation methods that are actively investigated, see e.g., [4], [5] published in this journal, multicarrier modulation in the form of orthogonal frequency division multiplexing (OFDM) has received a great deal of attention due to its promise for high data rate underwater acoustic communications; see e.g., performance results with experimental data in [6], [7], [8], [9], [10], [11]. The combination with multi-input and multi-output (MIMO) techniques has also been made to drastically increase the data rate through spatial modulation [12], [13], [14].

In this paper, we investigate the implementation of OFDM modems for underwater acoustic communications. First, we implement both single-input single-output (SISO) and multi-input multi-output (MIMO) OFDM modems on a floating-point TMS320C6713 DSP development board, running at 225 MHz. Through the work load analysis, we optimize the implementation to accelerate the decoding speed. Real-time operation has been achieved and the processing time for each OFDM block is much less than the block duration. We also examine the fixed-point implementation on a TMS320C6416 DSP development board for both SISO and MIMO systems. Running at a higher clock frequency (1 GHz) than TMS320C6713, the fixed-point implementation reduces the processing time by two thirds, with negligible performance degradation. Finally, we include some performance results with single transmitter and one or two receivers using data collected from the ACOMM10 experiment, conducted by Naval Research Laboratory (NRL) in an open sea area near New Jersey, July 2010.

There are a few acoustic modems available, including commercial products such as [15], [16], [17], a model widely used in the research community [18], and experimental designs such as [19], [20], [21], [22]. The designs in [15], [21], [22] are based on non-coherent frequency-shift-keying (FSK), and those in [16], [17], [20] are based on spread spectrum; all of them inherently have low data rate. The reconfigurable acoustic modem (rModem) of [19] has a flexible structure that can facilitate quick prototyping of different algorithms. The Micro-Modem of [18] has two operating modes: (1) a low-power low-rate mode based on non-coherent FSK, and (2) a high-power high-rate mode based on coherent phase-shift-keying (PSK). To the best of our knowledge, there is only one published paper on single-transmitter OFDM modem implementation [23] in addition to our initial effort in [24]. Both the receiver algorithms and the hardware platforms are different comparing [24] and [23]. So far, there is no reported result on MIMO-OFDM implementation except our result in [25].

The rest of this paper is organized as follows. We describe the OFDM transceiver design in Section 2. The results are presented in Section 3 for floating-point implementation and in Section 4 for fixed-point implementation. In Section 5, floating-point decoding performance based on sea test data is presented. Section 6 concludes the paper.

Section snippets

OFDM transceiver design

The DSP board supports stereo audio input and output, and hence up to two channels are available for transmission and reception. Based on this hardware configuration, we consider three settings: (1) a SISO system, (2) a single-input multi-output (SIMO) system with one transmitter and two receivers, and (3) a MIMO system with two transmitters and two receivers; note that the terms of SISO, SIMO, and MIMO are defined based on the numbers of inputs and outputs of the communication channel between

Floating-point implementation

We now describe the implementation results on a development board for the TMS320C6713 floating-point DSP. The DSP runs at 225 MHz.

Fixed-point implementation

For the fixed-point implementation, the DSP is TMS320C6416. Like TMS320C6713, it belongs to the TMS320C6000 family and has a VLIW architecture [29]. The TMS320C6414 chip can run at much higher clock rates than floating-point DSPs so it can reduce the execution time of many applications. In addition, the fixed-point implementation can facilitate future FPGA or ASIC implementations where fixed-point operations are adopted for smaller area and lower energy consumption. On the other hand, compared

Performance results replaying data from a sea test

In this section, we test the modem performance based on data collected from the ACOMM10 experiment conducted by the Naval Research Laboratory, July 2010. This experiment was done in an open sea, about 100 miles from the sea shore, near New Jersey. The water depth was about 70 m. The transmitter and receiver were placed about 50 m below the surface, and the distance between them was about 3 km. One transmitter was used, and there were eight phones on a receiver array to receive the signal. The

Conclusions

In this paper, we reported implementation results of SISO and MIMO OFDM acoustic modems using both floating- and fixed-point DSP platforms. Real-time decoding was achieved in all the considered cases. Nonbinary LDPC coding improves the performance relative to convolutional coding, at the cost of increased decoding time. Fixed-point implementation drastically reduces the processing time compared with the floating-point counterpart, running at a higher clock frequency. The floating-point decoding

Acknowledgments

We thank Ms. Janny Liao for her help on various implementation issues during the modem prototype development.

We thank Dr. T. C. Yang, Dr. Jeff Schindall, Mr. Tom Burchfield, and Mr. Robert Griffin for their help to collect the data from the NRL ACOMM10 experiment.

Hai Yan received the B.S. degree in Applied Physics in 1999 and the M.S. degree in Computer Sciences in 2003, both from the Wuhan University, Wuhan, China. He received his Ph.D. degree in Computer Science and Engineering from the University of Connecticut in 2010. He is currently working with Amazon. His research interests include wireless sensor networks, security and computer architecture.

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  • Cited by (0)

    Hai Yan received the B.S. degree in Applied Physics in 1999 and the M.S. degree in Computer Sciences in 2003, both from the Wuhan University, Wuhan, China. He received his Ph.D. degree in Computer Science and Engineering from the University of Connecticut in 2010. He is currently working with Amazon. His research interests include wireless sensor networks, security and computer architecture.

    Lei Wan was born in Jingdezhen City, China, in 1984. He received the B.S. degree in electrical information engineering from Tianjin University (TJU), Tianjin, China, 2006, and the M.Sc. degree in signal processing from the Beijing University of Posts and Telecommunications (BUPT), Beijing, China, 2009, and is currently working toward the Ph.D. degree in electrical and computer engineering at the University of Connecticut, Storrs. His main research focus is on algorithm design and implementation in OFDM underwater communication system.

    Shengli Zhou received the B.S. degree in 1995 and the M.Sc. degree in 1998, from the University of Science and Technology of China (USTC), Hefei, both in electrical engineering and information science. He received his Ph.D. degree in electrical engineering from the University of Minnesota (UMN), Minneapolis, in 2002. He has been an assistant professor with the Department of Electrical and Computer Engineering at the University of Connecticut (UCONN), Storrs, 2003–2009, and now is an associate professor. He holds a United Technologies Corporation (UTC) Professorship in Engineering Innovation, 2008–2011. His general research interests lie in the areas of wireless communications and signal processing. His recent focus is on underwater acoustic communications and networking. Dr. Zhou has served as associate editors for IEEE Transactions on Wireless Communications, Feb. 2005–Jan. 2007, and IEEE Transactions on Signal Processing, Oct. 2008–Sept. 2010, and is now an associate editor for IEEE Journal of Oceanic Engineering. He received the 2007 ONR Young Investigator award and the 2007 Presidential Early Career Award for Scientists and Engineers (PECASE).

    Zhijie Shi is currently an Associate Professor of Computer Science and Engineering at the University of Connecticut. He received his Ph.D. degree from Princeton University in 2004 and his M.S. and B.S. degrees from Tsinghua University, China, in 1996 and 1992, respectively. He is a member of IEEE and ACM. Professor Shi received US National Science Foundation CAREER award in 2006. His current research interests include underwater sensor networks, sensor network security, hardware mechanisms for secure and reliable computing, side channel attacks and countermeasures, and primitives for cipher designs.

    Jun-Hong Cui received her B.S. degree in Computer Science from Jilin University, China in 1995, her M.S. degree in Computer Engineering from Chinese Academy of Sciences in 1998, and her Ph.D. degree in Computer Science from UCLA in 2003. Currently, she is a faculty member of the Computer Science and Engineering Department at University of Connecticut. Her research interests cover the design, modeling, and performance evaluation of networks and distributed systems. Recently, her research mainly focuses on exploiting the spatial properties in the modeling of network topology, network mobility, and group membership, scalable and efficient communication support in overlay and peer-to-peer networks, algorithm and protocol design in underwater sensor networks. She is actively involved in the community as an organizer, a TPC member, and a reviewer for many conferences and journals. She has served as a guest editor for Elsevier Ad Hoc Networks on two special issues (one on underwater networks and the other on wireless communication in challenged environments). She now serves as an Associate Editor for Elsevier Ad Hoc Networks. She co-founded the first ACM International Workshop on UnderWater Networks (WUWNet’06), and she is now serving as the WUWNet steering committee chair. Jun-Hong received US NSF CAREER Award in 2007 and ONR YIP Award in 2008. She is a member of ACM, ACM SIGCOMM, ACM SIGMOBILE, IEEE, IEEE Computer Society, and IEEE Communications Society. More information about her research can be found at http://www.cse.uconn.edu/~jcui.

    Jie Huang was born in Jiangling, Hubei, P.R. China on January 20, 1981. He received the B.S. degree in 2001 and the Ph.D. degree in 2006, from the University of Science and Technology of China (USTC), Hefei, both in electrical engineering and information science. He was a post-doctoral researcher from July 2007 to June 2009, working with the Department of Electrical and Computer Engineering (ECE) at the University of Connecticut (UCONN), Storrs. Now he is a research assistant professor with the ECE Department at UCONN. His general research interests lie in the areas of communications and signal processing, specifically error control coding theory and coded modulation system design. His recent focus is on signal processing, channel coding and network coding for underwater acoustic communications and underwater sensor networks. Mr. Huang has served as a reviewer for the IEEE Transactions on Communications, the IEEE Transactions on Information Theory, the IEEE Transactions on Signal Processing, and the IEEE Journal on Selected Areas in Communications.

    Hao Zhou received the B.S. degree in 2004 and the Ph.D.degree in 2009, from the University of Science and Technology of China (USTC), Hefei, both in modern physics. He has been a post-doc with the Department of Electrical and Computer Engineering at the University of Connecticut (UCONN), Storrs since 2009. His general research interests lie in the areas of data acquisition and real-time signal processing. His recent focus is on the physical layer of underwater acoustic communications and networking.

    This work is supported by the ONR grant N00014-07-1-0805 (YIP), and the NSF grants CNS-0709005 (CRI) and CNS-0821597 (MRI). This work was partially presented at the ACM International Workshop on UnderWater Networks (WUWNet), Montréal, Québec, Canada, Sept. 2007 [24] and at the MTS/IEEE OCEANS Conference, Sydney, Australia, May 2010 [25].

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