Netted radar: Network communications design and optimisation

Networks of phased array radars are generally able to provide better counter stealth target detection and classification. Each radar sensor (or node) generates information which requires transmission to a central authority that is able to evaluate the information. This requires a communications network to be established to allow transmission of information to and from any node. Each radar node is limited by range and degree and relies on the formation of a multi-hop network to facilitate these transmissions.This paper presents a model whereby the radar beam itself is used in the formation of a multi-hop network. The phased array’s multi-functional nature allows rapid switching between communications and radar function. A model of how the communication system could operate is presented, and an evolutionary optimisation algorithm based upon the concept of Pareto optimality is used for the topological design of the network. Finally, a simulation environment is presented to show the simulated performance of the communication model and designed networks.     

Identification of AR parameters at a very low SNR using estimated spectral distribution in DCT domain

A simple and efficient method for system identification even at a very low signal-to-noise ratio (SNR) is presented. At an SNR as low as -7.5 dB, noise dominates the spectrum and system poles are almost lost in the profound noise. In the proposed method, an enhanced spectrum is estimated in the discrete cosine transform (DCT) domain using the least squares curve-fitting technique. The system modes that were previously indistinguishable become prominent in the enhanced spectrum. The system order is then overestimated using least squares higher order Yule-Walker (LSHOYW) equations to obtain better accuracy. The poles having higher strength in the autocorrelation domain are then identified as system poles.     

Validation of modal/MoM in shielding effectiveness studies of rectangular enclosures with apertures

This paper discusses the validation of Modal/method of moments (MoM) including cases when the apertures are made as big as the wall of the enclosure (equivalent to having one side of the cavity open). The validation is done using field computations involving bodies of arbitrary shape (FEKO), a commercially available code. The results show that Modal/MoM predicts the results close to the analytical results of Robinson et al. Electron. Lett., 32 (17), 1996; Robinson et al., IEEE Trans. Electromagn. Compat., 40 (3), 240-247, 1998 for single-aperture cases and for most double-aperture cases. Also, for the cases of considering oblique incident plane waves, through validation, it has been found that Modal/MoM can predict the shielding effectiveness close to measured results for smaller angles and not for larger angles of incidence due to the edge effects. In this work, the shielding effectiveness is calculated at only one point, the center of the cavity assuming it to be the worst case. This work discovers the limitation of Modal/MoM for certain applications.     

MIMO iterative receiver SNR estimation strategies for link to system interfacing

This paper presents link to system (L2S) interfacing technique for multiple input and multiple output (MIMO) iterative receivers. In L2S interfacing, usually the post detection signal to noise ratio (SNR)‐based frame error rate lookup tables (LUT) are used to predict the link level performance of receivers. While L2S interfacing for linear MIMO receivers can be conveniently implemented, it is more challenging for MIMO iterative receivers due to unavailability of the closed form SNR expressions. In this paper, we propose three methods for post detection SNR estimation for MIMO iterative receivers. The first is based on the QR decomposition of the channel matrix, the second relies on the residual noise calculation based on the soft symbols, and the third exploits the closed form SNR expressions for linear receivers. A link to system interface model for iterative receivers is developed for evaluating the reference curves for different modulation and coding schemes, and results are validated by comparing the simulated and predicted frame error rates. It is shown that linear and residual noise‐based SNR approximations result in a very good prediction performance whereas the performance of QR decomposition‐based method degrades for higher order modulations and coding schemes. This paper presents link to system interfacing technique for MIMO iterative receivers. A link to system interface model for iterative receivers is developed for evaluating the reference curves for different modulation and coding schemes, and results are validated by comparing the simulated and predicted frame error rates. Three post detection SNR evaluation schemes have been proposed for link to system interfacing all of which give good prediction performance especially at lower order modulation.     

Multi-Fidelity High-Throughput Optimization of Electrical Conductivity in P3HT-CNT Composites

Combining high-throughput experiments with machine learning accelerates materials and process optimization toward user-specified target properties. In this study, a rapid machine learning-driven automated flow mixing setup with a high-throughput drop-casting system is introduced for thin film preparation, followed by fast characterization of proxy optical and target electrical properties that completes one cycle of learning with 160 unique samples in a single day, a > 10 ×  improvement relative to quantified, manual-controlled baseline. Regio-regular poly-3-hexylthiophene is combined with various types of carbon nanotubes, to identify the optimum composition and synthesis conditions to realize electrical conductivities as high as state-of-the-art 1000 S cm⁻¹. The results are subsequently verified and explained using offline high-fidelity experiments. Graph-based model selection strategies with classical regression that optimize among multi-fidelity noisy input-output measurements are introduced. These strategies present a robust machine-learning driven high-throughput experimental scheme that can be effectively applied to understand, optimize, and design new materials and composites.     

SER and throughput analysis of space–time analog network coded relaying system over shadowed Rician fading channels

Wireless Networks - This research article presents an innovative approach based on analog network coding (ANC) in conjunction with space time block coding (STBC) which is termed as space time...     

Collision Free Mobility Adaptive (CFMA) MAC for wireless sensor networks

In this paper we propose high throughput collision free, mobility adaptive and energy efficient medium access protocol (MAC) called Collision Free Mobility Adaptive (CFMA) for wireless sensor networks. CFMA ensures that transmissions incur no collisions, and allows nodes to undergo sleep mode whenever they are not transmitting or receiving. It uses delay allocation scheme based on traffic priority at each node and avoids allocating same backoff delay for more than one node unless they are in separate clusters. It also allows nodes to determine when they can switch to sleep mode during operation. CFMA for mobile nodes provides fast association between the mobile node and the cluster coordinator. The proposed MAC performs well in both static and mobile scenarios, which shows its significance over existing MAC protocols proposed for mobile applications. The performance of CFMA is evaluated through extensive simulation, analysis and comparison with other mobility aware MAC protocols. The results show that CFMA outperforms significantly the existing CSMA/CA, Sensor Mac (S-MAC), Mobile MAC (MOB-MAC), Adaptive Mobility MAC (AM-MAC), Mobility Sensor MAC (MS-MAC), Mobility aware Delay sensitive MAC (MD-MAC) and Dynamic Sensor MAC (DS-MAC) protocols including throughput, latency and energy consumption.