Various approaches to analyze handover have been developed guarantee the quality of service multimedia services over mobile communication networks. However, no framework for multicarrier-based broadband systems, e.g., multicarrier code-division multiple access and orthogonal frequency-division access, is available based on perspective link capacity. This paper presents a technique referred as semisoft-handover-utilizing macroscopic diversity, which permits both hard soft advantages networks...

To achieve seamless multimedia streaming services over wireless networks, it is important to overcome inter-cell interference (ICI), particularly in cell border regions. In this regard scalable video coding (SVC) has been actively studied due its advantage of channel adaptation. We explore an optimal solution for maximizing the expected visual entropy orthogonal frequency division multiplexing (OFDM)-based broadband network from perspective cross-layer optimization. An optimization problem...

Due to the recent increasing utilization of deep learning models on edge devices, industry demand for Deep Learning Model Optimization (DLMO) is also increasing. This paper derives a usage strategy DLMO based performance evaluation through light convolution, quantization, pruning techniques and knowledge distillation, known be excellent in reducing memory size operation delay with minimal accuracy drop. Through experiments regarding image classification, we derive possible optimal strategies...

A recent dynamic increase in demand for wireless multimedia services has greatly accelerated the research on channel adaptation of high quality video applications. In this paper, we explore a theoretical approach to cross-layer optimization between and networks by means criterion termed ldquovisual throughputrdquo downlink transmission using layered coding algorithm. We obtain optimal loading ratio orthogonal frequency division multiple access (OFDMA) subcarriers through an problem balancing...

Compressive sensing (CS) makes it possible to more naturally create compact representations of data with respect a desired rate. Through wavelet decomposition, smooth and piecewise signals can be represented as sparse compressible coefficients. These coefficients then effectively compressed via the CS. Since transform divides image information into layered blockwise over spatial frequency domains, visual improvement attained by an appropriate perceptually weighted CS scheme. We introduce...

We propose the energy efficient MAC algorithm in this pa per. In proposed algorithm, each node sets contention window size with respect to residual energy, harvesting and transmit power. This makes sensor nodes consume their efficiently. To achieve goal, we use game theory cross-layer optimization. Introducing non-cooperative game, can formulate utility function easily. paper, allocate optimal power by optimization on PHY MAC.

Cross-layer optimization for efficient multimedia communications is an important emerging issue towards providing better quality-of-service (QoS) over capacity-limited wireless channels. This paper presents a cross-layer approach that operates between the application and physical layers to achieve high fidelity downlink video transmission by optimizing with respect quality criterion termed “visual entropy” using Lagrangian relaxation. By utilizing natural layered structure of wavelet coding,...

Various approaches for analyzing handover have been developed to guarantee the QoS (Quality of Service) multimedia services over mobile communication networks. However, no framework multicarrier-based broadband systems, such as MC-CDMA (Multi-Carrier Code Division Multiple Access) or OFDMA (Orthogonal Frequency is available, from perspective link capacity. This paper presents a technique, referred semi-soft utilizing macro diversity, which permits both hard and soft advantages networks be...

Compressive Sensing (CS) is a stable and robust technique that allows for the sub-sampling of data at given rate: `compressive sampling' or sensing' rates smaller than Nyquist sampling rate. It makes it possible to create standalone net-centric applications with fewer resources required in Internet Things (IoT). CS-based signal information acquisition/compression paradigm combines nonlinear reconstruction algorithm random on sparse basis provides promising approach compress systems. In this...

Compressive Sensing (CS) is a stable and robust technique that allows for the sub-sampling of data at given rate: `compressive sampling' or sensing' rates smaller than Nyquist sampling rate. It makes it possible to create standalone net-centric applications with fewer resources required in Internet Things (IoT). CS-based signal information acquisition/compression paradigm combines nonlinear reconstruction algorithm random on sparse basis provides promising approach compress systems. In this...

In this paper, we deal with a scheduling algorithm to fulfil qualified end-to-end video service in terms of fairness and energy efficiency over multi-hop wireless sensor networks. For goal, explore optimize the routing power allocation via cross-layer optimization by utilizing game-theoretic approach. order reduce computational complexity, also propose distributed algorithm. simulation results, demonstrate an improved performance proposed

Compressive Sensing (CS) is a stable and robust technique that allows for the sub-sampling of data at given rate: compressive sampling' or sensing' rates smaller than Nyquist sampling rate. It makes it possible to create standalone net-centric applications with fewer resources required in Internet Things (IoT). CS-based signal information acquisition/compression paradigm combines nonlinear reconstruction algorithm random on sparse basis provides promising approach compress systems. In this...

Wavelet image coding exhibits a robust error resilience performance by utilizing the naturally layered bitstream construction over band-limited channel. In this paper, closed form of visual entropy is defined based on weight wavelet domain, which characterized HVS (human vision system) frequency and spatial domains. This then utilized as criterion for determining order coefficients resulting improved quality demonstrated. terms entropy, transmission gain up to 20 % can be obtained at...

Compressive Sensing (CS) aims to recover a sparse signal from small number of projections onto random vectors. Because its great practical possibility, both academia and industries have made efforts develop the CS's reconstruction performance, but most existing works remain at theoretical study. In this paper, we propose new Block Compres-sive (nBCS), which has several benefits compared general CS methods. particular, nBCS can be dynamically adaptive varying channel capacity because it...

Compressive Sensing (CS) is a stable and robust technique that allows for the sub-sampling of data at given rate: `compressive sampling' or sensing' rates smaller than Nyquist sampling rate. while theoretical studies have demonstrated stability CS, specific examples successful practical applications remain elusive. In this paper, we apply multi-view images obtained from multiple visual sensor nodes to where measurement side emphasizes `important' CS in view 3D reconstruction. Due spatial...

Compressive Sensing (CS) is a stable and robust technique that allows for the sub-sampling of data at given rate: 'compressive sampling' or sensing' rates smaller than Nyquist sampling rate. It makes it possible to create standalone net-centric applications with fewer resources required in Internet Things (IoT). In this paper, we investigate how CS can provide new insights into coexisting heterogeneous IoT environments. First, briefly introduce theory respect through providing compressive...

We propose an adaptive video transmission scheme to achieve unequal error protection in a closed loop multiple input output (MIMO) system for wavelet-based coding. In this scheme, visual entropy is employed as quality metric agreement with the human (HVS), and associated weight used obtain set of optimal powers MIMO maximizing reconstructed video. For ease cross-layer optimization, sequence divided into several streams, importance each stream quantified using weight. Moreover, load balance...

For seamless multimedia streaming services, it is very important to overcome severe ICI (intercell interference) over wireless networks, particularly in the cell border region. SVC (scalable video coding) has been actively studied due its advantage of channel adaptation. In this paper, we study an optimal solution for maximizing expected visual entropy OFDM (orthogonal frequency division multiplexing)-based broadband network from aspect cross layer optimization. Based on approach, set source...

A smart exhibition guide service is to provide a guidance visitors by utilizing the environment composition, devices and mobile applications including web-based application. The enables each visitor create his own episode with respect article's contents, helps him fully understand narrative message from physical articles on exhibition. It also extends various relationships between articles, visitors, their Social Networking Services (SNS) in virtual world where make. In this paper,...

We present a face image deblurring framework for accurate facial landmark detection. In recognition application, performance is strongly affected by the detection accuracy of landmarks. Therefore, when developing algorithm, it important not only to improve restored quality, but also structural parts face. this work, we propose simple efficient network using Wavelet loss and Landmark-error related losses. Experimental results show that proposed has superior objective/subjective compared...

Cross-layer optimization for efficient multimedia communications has been an emerging issue, in terms of providing better QoS (quality service) over a capacity-limited wireless channel. This paper presents cross-layer approach between and network layers downlink image transmission by means quality criterion termed "visual entropy" using Lagrangian relaxation. By utilizing the natural layered structure wavelet coding, optimal level power allocation is determined, to permit throughput visual...