Srinivas Yerramalli

Optimal Resampling of OFDM Signals for Multiscale–Multilag Underwater Acoustic Channels

Underwater acoustic channels (UACs) have a large fractional bandwidth and are well modeled by a multiscale-multilag model, which is a generalization of the commonly employed single time-scale model. The path-dependent time scaling introduces significant channel variation, destroying carrier orthogonality and yielding intercarrier interference (ICI) in an orthogonal frequency division multiplexing (OFDM) system. Typical front-end processing at the receiver for a channel with common time scaling on every path involves resampling the received signal to compensate for this scaling. This work examines the choice of resampling parameter for the multiscale scenario. Bounds are derived for the performance and hard and soft data detection schemes using the Hammersley-Chapman-Robbins bound (HCRB) and the Cramér-Rao bound (CRB), respectively, which when optimized yield the optimal resampling parameter. It is shown that resampling is equivalent to matched filtering the incoming signal with an approximated channel having a common time scale on each path. A second criterion for optimizing the resampling parameter then minimizes the aggregate error between the multiscale channel and its single-scale approximation. Analysis of special cases suggests that the optimal resampling parameter is close to the time-scaling parameter of the dominant path. The scenarios under which using the time-scaling factor on the dominant path for resampling are suboptimal are also investigated. Blind and pilot-aided estimators for the optimal resampling parameter, which are a generalization of the estimators for the common time-scale model, are derived building on the channel approximation model for resampling. Numerical simulations show the advantages of the derived estimators over a classical packet-length-based time-scale estimator.

Partial FFT Demodulation: A Detection Method for Highly Doppler Distorted OFDM Systems

Employing Orthogonal Frequency Division Multiplexing (OFDM) signaling over time-varying channels results in inter-carrier interference (ICI) and degraded detection error probability due to the loss of orthogonality among the subcarriers. This problem is particularly exacerbated for systems operating in highly mobile scenarios such as underwater acoustic (UWA) communications, digital video broadcasting (DVB) for mobile devices and vehicle-to-vehicle (V2V) networks. To address the problem of data detection in such scenarios, we propose a novel demodulation strategy using several partial interval Fast Fourier Transforms (FFTs) instead of a conventional, single full interval FFT. Algorithms for computing the weights used to combine the outputs of the partial FFT are presented for three scenarios: full, partial and no knowledge of the time varying channel. Numerical simulations and an approximate theoretical analysis show that significant performance gains can be obtained over traditional equalizers at a very moderate complexity.

Distributed coordination and data fusion for underwater search

This paper presents coordination and data fusion methods for teams of vehicles performing target search tasks without guaranteed communication. A fully distributed team planning algorithm is proposed that utilizes limited shared information as it becomes available, and data fusion techniques are introduced for merging estimates of the targets position from vehicles that regain contact after long periods of time. The proposed data fusion techniques are shown to avoid overcounting information, which ensures that combining data from different vehicles will not decrease the performance of the search. Motivated by the underwater search domain, a realistic underwater acoustic communication channel is used to determine the probability of successful data transfer between two locations. The channel model is integrated into a simulation of multiple autonomous vehicles in both open ocean and harbor search scenarios. The simulated experiments demonstrate that distributed coordination with limited communication significantly improves team performance versus prior techniques that continually maintain connectivity.

Distributed Data Fusion for Multirobot Search

This paper presents novel data fusion methods that enable teams of vehicles to perform target search tasks without guaranteed communication. Techniques are introduced for merging estimates of a targets position from vehicles that regain contact after long periods of time, and a fully distributed team-planning algorithm is proposed, which utilizes limited shared information as it becomes available. The proposed data fusion techniques are shown to avoid overcounting information, which ensures that combining data from different vehicles will not decrease the performance of the search. Motivated by the underwater search domain, a realistic underwater acoustic communication channel is used to determine the probability of successful data transfer between two locations. The channel model is integrated into a simulation of multiple autonomous vehicles in both open water and harbor environments. The results demonstrate that the proposed distributed coordination techniques provide performance competitive with full communication.

On optimal resampling for OFDM signaling in doubly-selective underwater acoustic channels

Orthogonal frequency division multiplexing (OFDM) is under strong consideration as a modulation for underwater acoustic channels. Underwater acoustic channels are wideband in nature due to the fact that the signal transmission bandwidth is comparable to the carrier frequency. Furthermore, these channels are characterized by long delay spreads, sparsity and time variation. The time-variation challenges the use of OFDM - destroying carrier orthogonality and introducing significant inter carrier interference. Much of the current work on time varying channels assumes a single common Doppler shift for each path. As such, resampling is optimal preprocessing in such cases. The current work examines the choice of resampling factor for the case of distinct Doppler shift on each path. The optimal resampling factor is selected to maximize the Fisher information for the transmitted data; Fisher information is also used to evaluate the information loss due to resampling. The findings suggest that the optimal resampling factor is near that associated with the Doppler shift of the strongest path. It is also observed that the information loss is modest in many cases using this practical preprocessing.

Partial FFT demodulation: A detection method for doppler distorted OFDM systems

In mobile OFDM systems, such as underwater acoustic and digital video broadcasting (DVB) systems, time variation causes severe inter-carrier interference (ICI) which limits data detection performance. To address this problem, a signal processing strategy using several partial-interval FFTs instead of a conventional full-interval single FFT is proposed. Weighted combining of the partial FFT outputs coupled with standard OFDM processing, allows high performance symbol-by-symbol detection even in highly time-varying channels. Numerical examples show performance gains of several dB over a conventional receiver, thus indicating that an order of magnitude reduction in BER is achievable at a minimal increase in complexity.

Effects of underwater communication constraints on the control of marine robot teams

We address the effects of the aquatic communication channel constraints on the control performances of marine robot teams. The aquatic acoustic channels suffer from significant frequency and distance dependent attenuation, extensive time-varying multipath, motion-induced Doppler distortion and extreme channel latency due to the low speed of sound. Therefore, the available bandwidth is strongly limited and distance dependent. Due to all these limitations, the introduction of intra-vehicle exchanged information in the control loop of marine robots can degrade the overall system performance. We give an overview of the communication needs in the control of a marine robotic team. A realistic model of the aquatic communication channel is considered, and different limitations of the channel are addressed, e.g., message error rate and communication delays. An overview of the experimental test-bed that is used to study the communication characteristics of the aquatic channel is presented. Finally, we report on an extensive simulation study on the performance of a controller for a marine surface vessel which relies on an acoustic communication channel for information sensed at a distance.

Coalitional Games for Transmitter Cooperation in MIMO Multiple Access Channels

Cooperation between nodes sharing a wireless channel is becoming increasingly necessary to achieve higher throughputs in a wireless network. The problem of determining the feasibility and stability of cooperation between rational nodes in a wireless network is of great importance in understanding cooperative behavior. This paper addresses the stability of the grand coalition of transmitters signaling over a multiple access channel using the framework of cooperative game theory. The external interference experienced by each TX is represented accurately by modeling the cooperation game between the TXs in partition form. Single user decoding and successive interference cancelling strategies are examined at the receiver. Transmitter cooperation is stable, if and only if the core of the game (the set of all divisions of grand coalition utility such that no coalition deviates) is nonempty. Determining the stability of cooperation is a co-NP-complete problem in general. For a single user decoding receiver, transmitter cooperation is shown to be stable at both high and low SNRs, while for an interference cancelling receiver with a fixed decoding order, cooperation is stable only at low SNRs and unstable at high SNR. When time sharing is allowed between decoding orders, it is shown using an approximate lower bound to the utility function that TX cooperation is also stable at high SNRs. Thus, this paper demonstrates that ideal zero cost TX cooperation over a MAC is stable and improves achievable rates for each individual user.

Coalition games for transmitter cooperation in wireless networks

Cooperation between rational users has emerged as a new networking paradigm to improve the performance of wireless networks. In this paper, transmitter cooperation between wireless nodes in a Gaussian multiple access channel is studied under the framework of coalitional game theory. The stability of the grand coalition, the coalition of all users, is studied by modeling the game in partition form, in contrast to previous approaches using characteristic form games, in scenarios with infinite and finite cooperation capacity between transmitters. In both cases, irrespective of the channel gains, the grand coalition is shown to be the sum rate optimal and stable, in the sense that users do not have any incentive to leave the coalition.

Carrier Frequency Offset Estimation for Uplink OFDMA Using Partial FFT Demodulation

Fast and accurate Carrier Frequency Offset (CFO) estimation is a problem of significance in many multi-carrier modulation based systems, especially in uplink Orthogonal Frequency Division Multiple Access (OFDMA) where the presence of multiple users exacerbates the inter-carrier interference (ICI) and results in multi-user interference (MUI). In this paper, a new technique called partial FFT demodulation is proposed. Estimators for the CFO are derived by considering an approximated matched filter for each user, implemented efficiently using several FFTs operating on sub-intervals of an OFDM block. Through simulations, the feasibility and performance of the proposed estimators are demonstrated. Associated trade-offs are discussed.