Nonlinear channel codes are employed to protect two information fields that are related to the daylight saving time (DST) and leap second notifications within the enhanced WWVB broadcast format. The general codebook design criteria and the construction of these codes using integer linear program (ILP) is formulated. Specifically, two different variations are presented: i) minimizing the union bound of probability of word error (PWE), which is a tighter bound but has high computational complexity and ii) minimizing an analytical closed form approximation to the PWE, which has much lower complexity but is a looser bound on the exact PWE. By leveraging the highly non-uniform a-priori probabilities of the different messages being transmitted in these two fields, the proposed nonlinear codes provide coding gains of about 2-3 dB in the presence of additive white Gaussian noise (AWGN). When compared to checksum codes with the same rate, the nonlinear codes offer performance advantages of about 1-2 dB for the DST notification field. In the presence of impulsive noise, simulations and analysis show that the probability of word error when employing the proposed nonlinear code is lower by many orders of magnitude compared with that of the uncoded system.

In this paper, we propose a hypothesis testing based sequential frame synchronization technique that is robust against fluctuations and imperfect estimation of channel gain at the receiver. The proposed detector uses division in the decision rule to cancel the effect of channel gain, and therefore is called division based hypothesis testing (DHT). We show that the receiver operating characteristic (ROC) of DHT is close to the optimal likelihood ratio test (LRT), while the optimal LRT requires perfect knowledge of noise and channel gain at the receiver. Further, we use three performance metrics, namely, the probability of false synchronization Pfs, average reception duration lrx, and probability of missed synchronization Pms, to compare the performance of hypothesis testing against that of point estimation. We analytically show that hypothesis testing can have better reliability and lower energy consumption than point estimation if the probability of false alarm of the hypothesis testing is lower than the minimum of two thresholds. The cost of hypothesis testing is an arbitrarily small Pmswhile point estimation can have zero Pms. A modified implementation of hypothesis testing is also introduced to further reduce the energy consumption.

The architecture and algorithms for the first all-digital radio-controlled clock receiver for the new WWVB broadcast format are proposed. To address the potentially low signal-to-noise ratio conditions and the relatively large frequency offsets experienced in the receiver, two alternative timing synchronization approaches are investigated, i.e., one based on a maximum-likelihood (ML) criterion and the other based on correlation. We show that the correlation-based synchronization technique reduces the implementation complexity by over 50%, while its performance is only less than 1 dB inferior to that of the ML-based technique. Decision and detection algorithms are proposed for two operating regimes in the receiver: tracking and acquisition. In tracking, the proposed decision strategies reduce the timing mean squared error by as much as 63% compared with what the synchronizer produces without any additional processing. In acquisition, the proposed joint synchronization and decoding technique significantly improves the robustness by exploiting the channel code in the data. Compared with receivers based on the legacy broadcast, over 15 dB performance gains are achieved by the modulation and algorithms proposed for the tracking and acquisition operations. In addition to reception performance analyses, energy consumption tradeoffs are also presented.

In this paper, we propose a novel optimization framework for Roadside Unit (RSU) deployment and configuration in a vehicular network. We formulate the problem of placement of RSUs and selecting their configurations (e.g. power level, types of antenna and wired/wireless back haul network connectivity) as a linear program. The objective function is to minimize the total cost to deploy and maintain the network of RSU's. A user specified constraint on the minimum coverage provided by the RSU is also incorporated into the optimization framework. Further, the framework also supports the option of specifying selected regions of higher importance such as locations of frequently occurring accidents and incorporating constraints requiring stricter coverage in those areas. Simulation results are presented to demonstrate the feasibility of deployment on the campus map of Southern Methodist University (SMU). The efficiency and scalability of the optimization procedure for large scale problems are also studied and results shows that optimization over an area with the size of Cambridge, Massachusetts is completed in under 2 minutes. Finally, the effects of variation in several key parameters on the resulting design are studied.

An optimization scheme is developed for a cosine modulated perfect- reconstruction (PR) filter bank that is tailored to mitigate the effects of narrowband radio frequency interference (RFI). The conventionally used optimization criterion for bandpass filtering is to maximize the sidelobe attenuation by minimizing the stopband energy and minimizing the maximum stopband ripple. The proposed optimization scheme is designed particularly to combat RFI with completely known or partially known statistics. Simulation results for the scenario of strong narrowband RFI show that the proposed optimization scheme offers about 14% data rate improvement in the system's data throughput when compared to the traditional schemes.