This paper presents novel mobile phone antenna for radiations simultaneously in ten frequency bands for applications of LTE (Long-Term Evolution), GPS (Global Positioning System), GSM (Global System for Mobile Communications), PCS (Public and Commercial Services), DCS (Distributed Control System), UMTS (Universal Mobile Telecommunications System) and WiMAX (Worldwide Interoperability for Microwave Access). The antenna demonstrates novel characteristics for resolving the challenge of simultaneous radiation capabilities for the GSM and GPS applications with frequencies of 850/900 and 1575 MHz respectively, along with resonances at frequency band of 700 MHz for LTE applications, 1800 and 1900 MHz for PCS and DCS applications, 2100 MHz for UMTS applications, 2400 and 2500 MHz for LTE applications and 3300 MHz for WiMAX applications with S11 = - 6 dB matching criteria (VSWR 3:1). The antenna architecture comprises top and bottom copper layers embedded with monopole radiating element, branch line, slots and various stub lines. The desired operating bands are achieved in a compact area with overall dimensions of 0.8x60x120 mm for the height, width and length respectively of the antenna providing suitable platform for mobile handset applications. Omni-directional radiation pattern characteristics are achieved throughout the range of frequencies by designing the proposed antenna in monopole configuration. Proposed antenna is fabricated and results for the surface currents, s-parameters and 3D (Three-Dimensional) gain plots are illustrated for the proof of concept.
Compressive sensing is an approach to reduce the acquired signal dimension with a sampling rate lower than the Nyquist rate. This is achieved by incorporating suitable quantization techniques, such as scalar quantization, to compensate for the low sampling rate. However, quantization of small compressive sensing measurements does not perform well in terms of rate-distortion. This paper presents an adaptive variant of differential pulse code modulation coupled with scalar quantization for quantizing and de-quantizing the compressive sensing measurements of videos. The proposed adaptive approach along with scalar quantization allows reduction of the necessary bandwidth and provides a higher prediction gain than the conventional differential pulse code modulation. The performance of the proposed approach is validated by integrating with various compressive sensing reconstruction schemes and compared with the conventional video codec approach. The reconstructed video frames' visual quality using the proposed approach was also tested based on SSIM metric. The experimental result shows that the proposed scheme provides substantial gain over uniform scalar quantization, and scalar quantization with differential pulse code modulation at various compressive sensing measurements bitrates for different video sequences. When compared with conventional video compression schemes (containing side information at the encoder), the proposed Quantized CS approach shows notable improvements in reconstruction quality when compared with conventional video codecs at lower bitrates. In sum, the proposed methodology could contribute to benefit various battery powered application of visual sensor network in terms of low data processing, less power consumption and minimum memory utilization etc.
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