# R&D of an Innovative OFDM Communication Payload for Small-Size AUV
## 1 Introduction
However, this type of algorithms causes severe performance degradation while the estimated signal passes the frequency-selective fading channel. The classic cross-correlation estimation schemes realize extremely high-precision Doppler estimation in complex underwater multipath channel with calculating cross-ambiguity function (CAF) between transmitted and received packets [15; 16]. However, as the maximum CAF magnitude calculation is accomplished utilizing enormous searches in a two-dimensional grid of Doppler factors and delays, tremendous amounts of searching grids cause intensive computational complexity. In order to overcome the interference of enormous calculations, the stepwise cross-correlation estimation strategies (coarse estimation and fine estimation) were proposed and investigated, which can effectively reduce the number of searching grids and accelerate computation [17]. The single-branch auto-correlation (SBA) strategies have been extensively inquired to estimate Doppler factor through calculating the period variation of the periodical transmitted signal [18; 19]. However, the SBA approaches cannot be applied to scenarios where there is acceleration. With the purpose of expanding the applicability of the SBA methods, a multi-branch auto-correlation (MBA) algorithm [20] was proposed and investigated to address fast-moving and manoeuvring vehicles, the performance of which is comparable to that of the classic cross-correlation estimation schemes. An ultra-precision Doppler estimation strategy based on the minimum bit error rate (BER) principle was proposed and investigated to transform the signal-level Doppler estimation into the bit-level search [21]. With the purpose to restrain the massive BER searching, an iterative BER gradient descent algorithm [22] was investigated to accomplish the same estimation accuracy with the BER search strategy revealed in [21]. Nevertheless, this type of Doppler estimation strategy based on BER information requires the inclusion of a demodulation process in the process of Doppler estimation. Note that, while many more different types of investigations in Doppler estimation have been conducted, most of the previous work adopted resampling for Doppler compensation. In other words, after obtaining the Doppler factor via different types of estimation methods, Doppler compensation is generally realized by interpolation resampling in time domains according to the Doppler factor [23]. However, while it is relatively convenient to perform resampling using the software, considerable processing delays will be unavoidably generated. Thus, the agility of Doppler compensation poses a challenge for the design of the UWA OFDM system for AUV with agile moving capability or under rapidly time-varying UWA channels. With the purpose of enabling agile Doppler compensation, a hardware resampling scheme was designed to enable resampling via an adjustable sampling rate analog-to-digital Converter (ADC), which is driven by a precision-limited processor clock [24]. In this paper, by further improving the hardware resampling accuracy, a novel UWA OFDM communication payload based on STM32F407 processor is designed and implemented to facilitate agile Doppler compensation at the expense of low computational overhead. Specially, the proposed payload adopted a classic time-frequency OFDM receiver structure [25] with respect to simple implementation and low complexity onboard small-size AUV. Doppler estimation was accomplished with the classic method described in [23]. For agile and low computational overhead Doppler compensation, Direct Digital Frequency synthesizers (DDS) chip AD9954 controlled by STM32F407 processor is adopted to generate adjustable sampling clock frequency for ADC. The validity and superiority of the proposed scheme are verified through hardware-in-loop (HIP) simulation on the UWA OFDM modem that can be mounted properly on a small-size AUV platform. The rest of this paper is organized as follows.