Capacity Criterion-Based Bit and Power Loading for Shallow Water Acoustic OFDM System with Limited Feedback

In orthogonal frequency division multiplexing (OFDM) underwater acoustic (UWA) communications, some subcarriers may be subject to deep fading. If the channel state information (CSI) is available at the transmitter, adaptive transmission techniques can be applied to mitigate the deep fading effect and increase the system's overall performance. Therefore, it is more valuable to analyze the UWA channel with limited CSI feedback. In this paper, we adopt ambient noise in the OFDM UWA communication system for the first time and calculate its power for each subcarrier. We explain the properties of UWA channel and investigate the optimal power loading strategy for the UWA channel with different levels of transmitter's CSI, which is combined with bit loading for a given system target bit-error rate (BER). The optimum result is derived by maximum system capacity with the constraints of the system's total transmission power and target BER. The Lloyd algorithm is employed to quantize the CSI at the receiver and construct the codebook, which is also known to the transmitter. Simulation results compare the performance difference between a few bits of feedback, perfect feedback and non-feedback, which show that a few bits of feedback can significantly improve the system performance.

[1]  Milica Stojanovic,et al.  On the relationship between capacity and distance in an underwater acoustic communication channel , 2007, MOCO.

[2]  Allen Gersho,et al.  Vector quantization and signal compression , 1991, The Kluwer international series in engineering and computer science.

[3]  Robert W. Heath,et al.  OFDM power loading using limited feedback , 2005, IEEE Transactions on Vehicular Technology.

[4]  Victor B. Lawrence,et al.  OFDM with Pilot Aided Channel Estimation for Time-Varying Shallow Water Acoustic Channels , 2010, 2010 International Conference on Communications and Mobile Computing.

[5]  Dennis Goeckel Orthogonal Frequency Division Multiplexing for Wireless Communications , 2002 .

[6]  F. Digham,et al.  Performance of OFDM with M-QAM modulation and optimal loading over Rayleigh fading channels , 2004, IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004.

[7]  Guoqing Zhou,et al.  Simulation Analysis of High Speed Underwater Acoustic Communication Based on a Statistical Channel Model , 2008, 2008 Congress on Image and Signal Processing.

[8]  Wen-Bin Yang,et al.  M-ary frequency shift keying communications over an underwater acoustic channel: Performance comparison of data with models , 2006 .

[9]  Xiaopeng Huang,et al.  Capacity criterion-based power loading for underwater acoustic OFDM system with limited feedback , 2010, 2010 IEEE International Conference on Wireless Communications, Networking and Information Security.

[10]  Thomas J Hayward,et al.  Single- and multi-channel underwater acoustic communication channel capacity: a computational study. , 2006, The Journal of the Acoustical Society of America.

[11]  Victor B. Lawrence,et al.  Bandwidth-Efficient Bit and Power Loading for Underwater Acoustic OFDM Communication System with Limited Feedback , 2011, 2011 IEEE 73rd Vehicular Technology Conference (VTC Spring).

[12]  Milica Stojanovic,et al.  Statistical characterization and capacity of shallow water acoustic channels , 2009, OCEANS 2009-EUROPE.

[13]  Fan Zhang,et al.  Resource Allocation for Delay Differentiated Traffic in Multiuser OFDM Systems , 2008, IEEE Trans. Wirel. Commun..