Rapid prototyping of MIMO‐OFDM based on parity bit selected and permutation spreading

In this paper, a novel MIMO‐OFDM transmission scheme is developed to effectively enable multi‐access by joint code design across multiple antennas, subcarriers, OFDM frames, and users. It achieves better spectrum efficiency while improving bit error rate performance. The proposed scheme uses either parity bit selected or permutation techniques to assign spreading codes at the transmitter side. As a result, the detection at the receiver is greatly improved because of the fact that identifying the spreading code(s) directly yields the transmitted data symbols. The paper also investigates the field‐programmable gate array implementation of the proposed algorithms; optimization techniques are proposed to reduce area, power, and time. These techniques include a pipelined architecture for inverse FFT/FFT blocks, an efficient low complexity algorithm for despreading based on counters and comparators and an optimized architecture for complex matrix inversion using Gauss–Jordan elimination (GJ‐elimination). Finally, the fixed‐point optimized field‐programmable gate array architecture for MIMO‐OFDM transceiver is developed, where the maximum allowed performance loss because of quantization is defined, the tradeoffs between BER performance and area reduction are investigated. Copyright © 2015 John Wiley & Sons, Ltd.     

A projected fast ISTA algorithm for joint beam forming and antenna selection in massive MIMO

Wireless Networks - The joint beam-forming and antenna selection problem encountered in modern multi-user massive multiple input multiple output (MIMO) communication systems is solved using the...     

EARP: An Enhanced ACO-Based Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks

A plenty of Ant Colony Optimization (ACO)-based routing algorithms have been proposed to find optimal path of mobile sinks in Wireless Sensor Networks (WSNs). However, they concentrate on energy efficiency and ignore fault tolerance for critical data collection points like Cluster Heads (CHs). They supposed an ideal scenario where there are no failures which is not the case in reality due to failures resulting from unattended and hostile deployment environments and so on. Moreover, the existing routing protocols are not application-specific enabled (i.e., the parameters cannot be adapted to the application’s requirements). In this paper, we propose an energetically-optimized multi-sink-based clustered WSN model along with a fault-tolerant and energy-efficient Enhanced ACO based Routing Protocol (EARP) to provide reliable data transmission in case of encountering a faulty path. Unlike existing studies, EARP addresses jointly the different constraints of forest fires detection application like fault tolerance, network lifetime and response time. The proposed EARP is simulated along with its counterparts in a general scenario based on various main metrics and also in an application-specific scenario (forest fires detection) based on network lifetime and response time. The simulations results prove its superiority, compared to its peers, in both scenarios.

     

A 7-dB 43-GHz CMOS Distributed Amplifier on High-Resistivity SOI Substrates

This paper presents designs and measurements of distributed amplifiers (DAs) processed on a 130-nm silicon-on-insulator CMOS technology on either standard-resistivity (10 Omegamiddotcm) or high-resistivity (>1 kOmegamiddotcm) substrates, and with either body-contacted (BC) or floating-body (FB) MOSFETs. Investigations have been carried out to assess the impact of active device performance and transmission line losses on circuit design by means of simulations, analytical calculations, and comparisons of the small-signal equivalent-circuit parameters. On standard-resistivity substrates, DAs with FB devices and lossy microstrip lines on thin film exhibit a measured gain of 7.1 dB and a unity-gain bandwidth (UGB) of 27 GHz for a dc power consumption of 57 mW. With the introduction of high-resistivity substrates, other DAs, with the same architecture and using lower loss coplanar waveguide lines, show a UGB of 51 GHz with FB devices and 47 GHz with BC devices. To the authors' knowledge, the designs presented in this paper achieve the best tradeoffs in terms of gain, bandwidth, and power consumption for CMOS-based circuits with comparable architecture.     

Synthesis of ZnO nanostructure films by thermal evaporation approach and their application in dye-sensitized solar cells

Zinc oxide (ZnO) films were prepared successfully by simple thermal evaporation of zinc acetate dihydrate at low temperature onto FTO (fluorine-doped tin oxide) glass substrates coated with thin ZnO seed layer. The synthetic parameter such as temperature was found to determine the morphology of nanostructures. ZnO nanorod (NR) and nanoparticle (NP) films have been synthesized at 245 and 350 °C, respectively, for 6 h. The dye-sensitized solar cells (DSSCs) were fabricated using the ZnO nanostructure films as photosensitized electrodes. A maximum photoelectric conversion efficiency (PCE) of 1.56%, and short-circuit photocurrent density of 5.12 mA/cm² were achieved with the ZnO NP-based DSSC. The PCE increase was ascribed to the reduced recombination loss and prolonged electron lifetime according to electrochemical impedance spectroscopy (EIS).     

An energy efficient Genetic Algorithm based approach for sensor-to-sink binding in multi-sink wireless sensor networks

Wireless sensor networks (WSNs) are ad-hoc networks in which sensors, that are designed to relay data back to sink nodes and/or Base Stations, are deployed in an area and may be configured in real time. Sensors, however, have limited energy supplies and are often left untouched after deployment, thus making battery replacement very difficult or even impossible. Therefore, energy should be efficiently conserved to extend the WSNs lifetime. One of the existing solutions is to deploy multiple sinks, more capable nodes in comparison to sensors, in the network to increase the coverage area and shorten the communication distance between sensors and sinks. However, this raises the issue concerning which sensors should bind to which sinks in order to avoid overloading particular sinks. In this paper, we devise a Genetic Algorithm based approach to solve the problem of balancing the load of sensors amongst sinks in a multi-sink WSN, while ensuring that the best routes to sinks are found for the sensors that cannot directly reach a sink. We evaluate the performance of our approach and compare it to an existing one using the network simulator NS-2 through measuring several metrics such as the variance of remaining energy among sinks, and energy consumption in sinks. The obtained results show that the proposed approach promising.