Distributed spatial diversity enabled receiver system

The prime functionality of underwater acoustic modems is communication. It is known that spatial diversity can provide improved communication performance, in the form of increased data rate or extended range. While spatial diversity is traditionally harnessed by having multiple antennas connected to a single modem, we showed through this work that multiple receiver modems can also be used cooperatively to leverage spatial diversity. One can also get much larger separation between modems than possible with multi-antenna systems. We designed a framework, implemented designed protocol and the carried out experiments at sea. The system comprises of spatially separated receivers exchanging the information received over the long-range underwater acoustic link to cooperatively decode the received information. The receivers cooperate over a short-range wired/wireless network to share the received copy of signals and decode the information transmitted. The performance results of this distributed spatial diversity receiver system shows that in practice this technique improves the communication performance significantly in terms of either reliability, data rate or range.

Related blog article: blog.unetstack.net/exploting-spatial-diversity-using-unetstack3

Related publication:

P. Anjangi, M. Chitre, M. Ignatius, C. Pendharkar 2021, September. Distributed Spatial Diversity Enabled Receiver System for an Underwater Acoustic Link. In 2021 Fifth Underwater Communications and Networking Conference (UComms) (pp. 1-5). IEEE. (Presented at IEEE UComms'21) [click here to watch]

Related patent: Anjangi Prasad, Chitre Mandar, Ignatius Manu, Pendharkar Chinmay, A Receiver System and a Method for Receiving a Transmitted Signal via a Long Range Link., 24 September 2020.} (International application published under the Patent Cooperation Treaty (PCT)).

Underwater localization and tracking

A common problem in mobile robotics deals with answering the question: “Where am I?”. If the robot is equipped with GPS (Global Positioning System) receiver, it can be localized accurately. Unfortunately, GPS doesn’t work underwater. For GPS to work underwater, the GPS receiver should be able to receive the Radio Frequency (RF) signals from GPS satellites. But RF signals do not propagate well in water and therefore GPS receiver cannot receive the signals underwater. Acoustic communication is the most promising mode of communication underwater. With static reference underwater acoustic modems acting as “satellites” in the ocean, we can localize an underwater robot/vehicle. I have over the course of my postdoctoral experience worked on variety of underwater localization problems such as diver communication and localization, ROV localization while cleaning ship hull and Ultra-short baseline systems.

Diver communication and localization:

Diving operations are still predominant today in many underwater applications despite the advances in robot-assisted technologies. Apart from being invaluable in carrying out many complex tasks underwater, diving is also a popular form of recreational activity. To improve diver safety and enable new scenarios under which divers can operate, a robust and reliable communication and localization system is extremely useful. Communicating from the surface to divers, and between divers themselves, is a challenge.

Currently, most commercial diving operations rely on rudimentary communication using hand signals and floats among the divers. In order to communicate with the topside application (e.g. topside manager) of the dive operation from the surface, tethered systems are used. Dive logs including the depth, pressure, etc., are measured using dive computers but to monitor these parameters and track the divers in real-time on the surface, is a challenge. This can be resolved using the advances made in underwater acoustic communications. There is a strong need for a system capable of logging basic diver statistics and providing real-time feedback of the location and condition of the divers, to enhance the safety and effectiveness of dive operations. A diver communication and localization solution that allows two-way communication between the topside application and the divers with simultaneous localization of the divers is designed, implemented, and demonstrated. The proposed system allows the topside manager to monitor real-time dive parameters including diver’s depth, location, and tank pressure.

Related blog article: https://blog.unetstack.net/on-underwater-localization-using-unetstack

Related publication:

P. Anjangi et.al, 2020, August. ”Diver Communications and Localisation System Using Underwater Acoustics”. in IEEE Global Oceans’20, (Singapore, Gulf Coast U.S.), October 2020.

Machine learning-based adaptive modulation

Underwater acoustic channels are fast varying in both spatial and temporal domain and hence are characterized by non-stationary fading statistics. When the channel statistics change, a modulation scheme designed for a specific fading model will underperform which motivates the need for link tuning algorithms. In order to alleviate this problem, data-driven adaptive modulation techniques are studied previously. Since channel information is unknown, these algorithms solve the explore-exploit dilemma in order to take actions that result in maximizing the average data rate. Channel physics information is often ignored in the design of these algorithms. The information gained through channel physics such as delay spread, coherence time, doppler spread etc. of the channel plays an important role in narrowing down the search space of modulation scheme parameters. However, the channel physics by itself is not sufficient to find a good-performing solution. Therefore, we develop a hybrid algorithm that utilizes both, the information gained from channel physics and techniques from data-driven algorithms to solve the explore-exploit dilemma. A simplified Orthogonal Frequency Division Multiplexing (OFDM) system is used to illustrate the concept and its parameters are tuned in an online fashion. In particular, an online learning algorithm is developed to track the goodness of the schemes and a multi-armed bandit-like problem is solved for taking decisions sequentially in order to maximize the average data rate of an underwater acoustic (UWA) communication link.

Related publications:

P. Anjangi., Chitre, M. (2018, August). ”Model-based Data-driven Learning Algorithm for Tuning an Underwater Acoustic Link”. In 2018 Fourth Underwater Communications and Networking Conference (UComms) (pp. 1-5). IEEE. (Lerici, Italy).

S Wu., Chitre, M., P. Anjangi. (2018, August). ”Monte Carlo Tree Search and Delay-Aware Feedback Adaptation for Underwater Acoustic Link Tuning ”. In 2021 IEEE Global Oceans 2021 San Diego - Porto.