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Localization of wireless transmitters is traditionally done using Radio Frequency (RF) sensors that measure the propagation delays between the transmitter and a set of anchor receivers. One of the major challenges of wireless localization systems is the need for anchor nodes to be time-synchronized to achieve accurate localization of a target node. Using a reference transmitter is an efficient way to synchronize the anchor nodes Over-The-Air (OTA), but such algorithms require multiple periodic messages to achieve tight synchronization. In this paper, we propose a new synchronization method that only requires a single message from a reference transmitter. The main idea is to use the Carrier Frequency Offset (CFO) from the reference node, alongside the Time of Arrival (ToA) of the reference node messages, to achieve tight synchronization. The ToA allows the anchor nodes to compensate for their absolute time offset, and the CFO allows the anchor nodes to compensate for their local oscillator drift. Additionally, using the CFO of the messages sent by the reference nodes and the target nodes also allow us to estimate the speed of the targets. The error of the proposed algorithm is derived analytically and is validated through controlled laboratory experiments. Finally, the algorithm is validated by realistic outdoor vehicular measurements with a software-defined radio testbed. [ABSTRACT FROM AUTHOR]

The complexity of electronic systems for RF and digital applications is ever increasing, and the corresponding compliance analysis for ensuring the required specifications in terms of performances, signal and power integrity is a challenging task often accomplished by relying on commercial circuit simulators. The modeling of multiport devices involves the assembly of electrical networks usually described in terms of S‐parameter. This work proposes a new single‐step algorithm that computes the global S‐parameter matrix for a cascade of multiple networks with multiple ports without the need of any S‐parameter transformation in T‐parameters and their inverse transformation. The proposed method involves the construction of a large matrix filled with all S‐parameters of all networks, and the subsequent evaluation of only one matrix expression. The proposed method is shown to be very efficient and reliable, since it can be easily automated without the need of a manual connections of tens or even hundreds of ports of the multiple blocks, which is an action that needs to be performed within a typical circuit simulator environment. Also, the proposed method overcomes the limitation of the standard method based on S‐to‐T parameter transformation since it is of general applicability to networks with different number of input and output ports. Examples involving the cascade of multiple 2‐ports and multiports networks are considered, and the results are validated and compared with the reference results obtained from a commercial circuit simulator. The proposed method is shown to be effective and fast compared to its counterpart based on the T‐parameters. [ABSTRACT FROM AUTHOR]

We present a new formulation of the doubly orthogonal matching pursuit (DOMP) algorithm for the sparse recovery of Volterra series models. The proposal works over the covariance matrices by taking advantage of the orthogonal properties of the solution at each iteration and avoids the calculation of the pseudoinverse matrix to obtain the model coefficients. A detailed formulation of the algorithm is provided along with a computational complexity assessment, showing a fixed complexity per iteration compared with its previous versions in which it depends on the iteration number. Moreover, we empirically demonstrate the reduction in computational complexity in terms of runtime and highlight the pruning capabilities through its application to the digital predistortion of a class J power amplifier operating under 5G-NR signals with the bandwidth of 20 and 30 MHz, concluding that this proposal significantly outperforms existing techniques in terms of computational complexity. [ABSTRACT FROM AUTHOR]

This paper proposes a new approach of digital predistortion (DPD) technique based on the adaptive indirect learning architecture (ILA) by using a recursive prediction error minimization (RPEM) algorithm for linearizing radio frequency (RF) power amplifiers (PAs) in emerging wideband communication systems. In the proposed RPEM-based linearization approach, the forgetting factor varies with time and is less sensitive to noise. Therefore, the predistorter (PD) parameter estimates become more consistent and accurate in steady state so that the mean square errors can be reduced. Both the error vector magnitude (EVM) and the adjacent channel power ratio (ACPR) are used to evaluate the DPD technique in RF PAs employing the proposed linearization. The efficiency validation of the proposed method is based on a simulated PA Wiener model. The simulation results have clarified the improvement of the proposed adaptive ILA-based DPD with RPEM algorithm in terms of both EVM and ACPR. [ABSTRACT FROM AUTHOR]

The node-disjoint paths problem deals with finding node-disjoint paths from a source node s to target node t, where t ≠ s. Two paths from s to t are said to be node-disjoint i ff they do not have any common vertices except for their endpoints. Distributed solutions to the node-disjoint paths problem have numerous applications such as secure message transmission, reliable routing, and network survivability. In this paper, we present a simple distributed algorithm that is both stabilizing and inherently stabilizing under a realistic model that describes system interfaces and implementation issues in detail to route messages over all shortest node-disjoint paths from one process to another in an n-dimensional hypercube network. [ABSTRACT FROM AUTHOR]