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Over the last few years there has been growing interest in performing channel estimation via superimposed training (ST), where a training sequence is added to the information-bearing data, as opposed to being time-division multiplexed with it. Recent enhancements of ST are data-dependent ST (DDST), where an additional data-dependent training sequence is also added to the information-bearing signal, and semiblind approaches based on ST. In this paper, along with the channel estimation, we consider new algorithms for training sequence synchronization for both ST and DDST and block (or frame) synchronization (BS) for DDST (BS is not needed for ST). The synchronization algorithms are based on the structural properties of the vector containing the cyclic means of the channel output. In addition, we also consider removal of the unknown dc offset that can occur due to using first-order statistics with a non-ideal radio-frequency receiver. The subsequent bit error rate (BER) simulations (after equalization) show a performance not far removed from the ideal case of exact synchronization. While this is the first synchronization algorithm for DDST, our new approach for ST gives identical results to an existing ST synchronization method but with a reduced computational burden. In addition, we also present analysis of BER simulations for time-varying channels, different modulation schemes, and traditional time-division multiplexed training. Finally, the advantage of DDST over (conventional, non semi-blind) ST will reduce as the constellation size increases, and we also show that even without a BS algorithm, DDST is still superior to conventional ST. However, iterative semiblind schemes based upon ST outperform DDST but at the expense of greater complexity.

This paper develops an architecture for flying ad-hoc networks (FANETs) to enable monitoring of water quality in a shrimp farm. Firstly, the key monitoring parameters for the characterization of water quality are highlighted and their desired operational ranges are summarized. These parameters directly influence shrimp survival and healthy growth. Based on the considered sensing modality, a reference architecture for implementing a cost-effective FANET based mobile sensing platform is developed. The controlled mobility of the platform is harnessed to increase the spatial monitoring resolution without the need for extensive infrastructure deployment. The proposed solution will be offered to shrimp farmers in the Mexican state of Colima once the laboratory trials are concluded.

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This paper proposes a blind interference cancellation algorithm that is able to provide multiple packet reception capability for asynchronous random access wireless mobile ad hoc networks. The algorithm exploits the fact that the baseband signal exhibits cyclostationarity properties, which are induced at the transmitters by means of modulating the symbols with polynomial phase sequences. This modulation does not expand the bandwidth and can be considered as a "color code" that can be used to distinguish one transmission from the others (i.e., packets from other users). The proposed technique does not require knowledge of the starting time of transmission of the desired signal and can also be applied to time-dispersive multipath channels. In addition, a practical way of assigning the color codes via the use of a common codebook known to all nodes is proposed, and the impact on local throughput of such a scheme is analyzed. Simulation results illustrate the excellent performance of the proposed approach.