Capacity analysis of underwater acoustic MIMO communications

Multi-Input Multi-Output (MIMO) principle is based on transmitting digital data from Nt transmitters to Nr receivers within a frequency band. In the last decade, theoretical works and practical experiments in wireless and cellular networks have convincingly proved that MIMO has been a real find in digital communications. Nowadays, MIMO principle is being applied to underwater acoustic communications (UAC) and it is showing encouraging results. But very few research has been done on the relation between different parameters of MIMO and its gain. Our primary purpose in this project is to analyse the MIMO gain theoretically using Shannon capacity analysis and suggest ways to maximize capacity with limited bandwidth by varying other parameters . As we will show in the later pages of this project that underwater acoustic channel (UAC) is highly selective in frequency, data transmission cannot be increased by simply increasing the transmission bandwidth. This difficult situation can be found in wireless communication where there is an increasingly large requirement in high speed data transfer but available bandwidth is constrained by the frequency allocation law. In those communication fields where radio frequency is used , this bandwidth limitation problem has been overcome by introducing MIMO techniques, which provide significant gain in data transmission rate while keeping the transmission Bandwidth constant.In the previous years, the contribution of MIMO to UAC systems has mostly been thoroughly analyzed via spatial modulation or multi-carrier modulation. Initial simulation and experimental results have showcased a larger gain over conventional single input single output (SISO) but the results strongly vary depending on the modulation scheme chosen by us and the receiver algorithm as well as the underwater channel environment

Investigation of Parameters Affecting Underwater Communication Channel

Underwater communication has become a widely studied area in recent years and showed great potential to be an area of research. Acoustic communication is often preferred in underwater communication due to its suitability for an underwater diffusion environment. However, in underwater communication, the physical and chemical properties of the water environment affect sound propagation. Therefore, determining and examining parameters affecting channel performance in underwater communication plays an essential role in inefficient communication. In this study, the effects of salinity, depth, noise, temperature, and frequency parameters for the underwater channel model are examined. By determining the effects of these parameters on spherical and cylindrical propagation, suitable propagation geometry and parameter values for an efficient channel are investigated. In light of the results obtained, in case of studying in a limited area, the path and absorption losses can be reduced by selecting cylindrical propagation as a geometrical propagation model, thereby an efficient channel model can be formed

Underwater acoustic channel properties in the Gulf of Naples and their effects on digital data transmission

In this paper we studied the physical properties of the Gulf of Naples (Southern Italy) for its use as a commu- nication channel for the acoustic transmission of digital data acquired by seismic instruments on the seafloor to a moored buoy. The acoustic link will be assured by high frequency acoustic modems operating with a central frequency of 100 kHz and a band pass of 10 kHz. The main operational requirements of data transmission con- cern the near horizontal acoustic link, the maximum depth of the sea being about 300 m and the planned hori- zontal distance between seismic instruments and buoy 2 km. This study constructs the signal-to-noise ratio maps to understand the limits beyond which the clarity of the transmission is no longer considered reliable. Using ray- theory, we compute the amplitudes of a transmitted signal at a grid of 21×12 receivers to calculate the transmis- sion loss at each receiver. The signal-to-noise ratio is finally computed for each receiver knowing also the trans- mitter source level and the acoustic noise level in the Gulf of Naples. The results show that the multipath effects predominate over the effects produced by the sound velocity gradient in the sea in the summer period. In the case of omnidirectional transmitters with a Source Level (SL) of 165 dB and a baud rate of 2.4 kbit/s, the results al- so show that distances of 1400-1600 m can be reached throughout the year for transmitter-receiver connections below 50 m depth in the underwater acoustic channel

BER Performance Improvement in UWA Communication via Spatial Diversity

In present era while wireless communication has become an integral part of our life, the advancements in underwater communications (UWA) is still seem farfetched. Underwater communication is typically essential because of its ability to collect information from remote undersea locations. It don’t use radio signals for signal transmission as they can propagate over extremely short distance because of degradation in signal strength due to salinity of water, rather it uses acoustic waves. The underwater acoustic channel has many characteristics which makes receivers very difficult to be realized. Some of the characteristics are frequency dependent propagation loss, severe Doppler spread multipath, low speed of sound. Due to motion of transmitter and receiver the time variability and multipath makes underwater channel very difficult to be estimated. There are various channel estimation techniques to find out channel impulse response but in this thesis we have considered a flat slow fading channel modeled by Nakagami-m distribution. Noise in underwater communication channel is frequency dependent in nature as for a particular range of frequency of operation one among the various noise sources will be dominant. Here they don’t necessarily follow Gaussian statistics rather follows Generalized Gaussian statistics with decaying power spectral density. The flexible parametric form of this statistics makes it useful to fit any source of underwater noise source. In this thesis we have gone through two step approach. In the first step, we have considered transmission of information in presence of noise only and designed a suboptimal maximum likelihood detector. We have compared the performance of this proposed detector with the conventional Gaussian detector where decision is taken based on a single threshold value and the threshold value is calculated by using various techniques. Here it is being observed that the ML detector outperforms the Gaussian detectors and the performance can be improved further by exploiting the multipath components. In the second step we have considered channel along with noise and have designed a ML detector where we have considered the receiver is supplied with two copies of the same transmitted signal and have gone through a two-dimensional analysis. Again we compared the performance with conventional maximal ratio combiner where we can observe the ML detector performance is better. Further we have incorporated selection combining along with these detectors and compared the performance. Simulation results shows that the proposed detector always outperforms the existing detectors in terms of error performance

Short-Range Underwater Acoustic Communication Networks

This chapter discusses the development of a short range acoustic communication channel model and its properties for the design and evaluation of MAC (Medium Access Control) and routing protocols, to support network enabled Autonomous Underwater Vehicles (AUV). The growth of underwater operations has required data communication between various heterogeneous underwater and surface based communication nodes. AUVs are one such node, however, in the future, AUV’s will be expected to be deployed in a swarm fashion operating as an ad-hoc sensor network. In this case, the swarm network itself will be developed with homogeneous nodes, that is each being identical, as shown in Figure 1, with the swarm network then interfacing with other fixed underwater communication nodes. The focus of this chapter is on the reliable data communication between AUVs that is essential to exploit the collective behaviour of a swarm network

Space-time-frequency methods for interference-limited communication systems

textTraditionally, noise in communication systems has been modeled as an additive, white Gaussian noise process with independent, identically distributed samples. Although this model accurately reflects thermal noise present in communication system electronics, it fails to capture the statistics of interference and other sources of noise, e.g. in unlicensed communication bands. Modern communication system designers must take into account interference and non-Gaussian noise to maximize efficiencies and capacities of current and future communication networks. In this work, I develop new multi-dimensional signal processing methods to improve performance of communication systems in three applications areas: (i) underwater acoustic, (ii) powerline, and (iii) multi-antenna cellular. In underwater acoustic communications, I address impairments caused by strong, time-varying and Doppler-spread reverberations (self-interference) using adaptive space-time signal processing methods. I apply these methods to array receivers with a large number of elements. In powerline communications, I address impairments caused by non-Gaussian noise arising from devices sharing the powerline. I develop and apply a cyclic adaptive modulation and coding scheme and a factor-graph-based impulsive noise mitigation method to improve signal quality and boost link throughput and robustness. In cellular communications, I develop a low-latency, high-throughput space-time-frequency processing framework used for large scale (up to 128 antenna) MIMO. This framework is used in the world's first 100-antenna MIMO system and processes up to 492 Gbps raw baseband samples in the uplink and downlink directions. My methods prove that multi-dimensional processing methods can be applied to increase communication system performance without sacrificing real-time requirements.Electrical and Computer Engineerin