Millimeter wave (mmWave) multiple-input-multiple-output (MIMO) systems will almost certainly use hybrid precoding to realize beamforming with few numbers of RF chains to reduce energy consumption, but require low complexity technique to improve spectral efficiency. While energy-efficient hybrid analog/digital precoders and combiners designs can subdue the high pathloss inherent in mmWave channels, they assume the use of infinite-(or high-) resolution phase shifters to realize the analog precoder and combiner pair which results in high hardware cost and power consumption. One promising solution is to employ the use of low-resolution phase shifters. In this paper, we first diverse the exploration of multiple candidates of array response vectors, to propose low-complexity hybrid precoder and combiner (LcHPC) design via stage-determined matching pursuit (SdMP) namely, LcHPC-SdMP for pursuing better achievable rate for mmWave MIMO systems. We initially decouple the joint optimization over hybrid precoders and combiners into two separate sparse recovery problems. Specifically, LcHPC-SdMP algorithm revises the identification step of orthogonal matching pursuit (OMP) to the selection of multiple ''correct'' column indices of the matrix of array response vectors, per iteration. Then adds a pruning step −after satisfying a sparsity level condition, to iteratively refine the sparse solution which aids in further accelerating the algorithm, by requiring fewer iterations. We then propose an algorithm which iteratively designs low-resolution (two-bit) hybrid analog-digital precoder and combiner (LrHPC), for pursuing efficiency while maximizing spectral efficiency. Simulation results demonstrate that the proposed LcHPC-SdMP algorithm performs very close to its full-digital precoding and achieves better spectral efficiency over state-of-the-art algorithms with a substantially reduced number of iteration than the recently proposed schemes. In addition, simulation results also reveal that the achievable rate of the proposed LrHPC algorithm is higher than those of the existing algorithms under consideration.
<em><span lang="EN-AU">Smart home control system can be integrated into an existing home appliances to reduce the need for human intervention, increase security and energy efficiency. However, it is still an open problem due to difficulties such as network distance, signal interference, not user friendly, increased cost and power consumption. This paper reviews various topics on smart home technologies including control system, smart home network, smart home appliance and sensor technologies for smart home. In this research, the proposed prototype of home automation allows users to remotely switch on or off any household appliance based on Internet of Things (IoT) with the enhancement of solar charger. The smartphone and/or tablet replaces the manual use of personal computer without the need for high additional cost. This prototype uses four types of sensors i.e. PIR sensor, temperature sensor, ultrasonic sensor and smoke gas sensor for automatic environmental control and intrusion detection.</span></em>
<p><em>Nowadays, image manipulation is common due to the availability of image processing software, such as Adobe Photoshop or GIMP. The original image captured by digital camera or smartphone normally is saved in the JPEG format due to its popularity. JPEG algorithm works on image grids, compressed independently, having size of 8x8 pixels. For unmodified image, all 8x8 grids should have a similar error level. For resaving operation, each block should degrade at approximately the same rate due to the introduction of similar amount of errors across the entire image. For modified image, the altered blocks should have higher error potential compred to the remaining part of the image. The objective of this paper is to develop a photo forensics algorithm which can detect any photo manipulation. The error level analysis (ELA) was further enhanced using vertical and horizontal histograms of ELA image to pinpoint the exact location of modification. Results showed that our proposed algorithm could identify successfully the modified image as well as showing the exact location of modifications.</em></p>
A method for fabricating single crystal silicon nanowires is presented using top-down optical lithography and anisotropic etching. Wire diameters as small as 10 nm are demonstrated using silicon on insulator substrates. Structural characterization confirms that wires are straight, have a triangular cross section and are without breakages over lengths of tens of microns. Electrical characterization indicates bulk like mobility values, not strongly influenced by surface scattering or quantum confinement. Processing is compatible with conventional silicon technology having much larger critical dimensions. Integrating such nanowires with a mature CMOS technology offers an inexpensive route to their exploitation as sensors. V
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