In this paper, we investigate the problem of power control for streaming variable bit rate (VBR) videos over wireless links. A system model involving a transmitter (e.g., a base station) that sends VBR video data to a receiver (e.g., a mobile user) equipped with a playout buffer is adopted, as used in dynamic adaptive streaming video applications. In this setting, we analyze power control policies considering the following two objectives: 1) the minimization of the transmit power consumption and 2) the minimization of the transmission completion time of the communication session. In order to play the video without interruptions, the power control policy should also satisfy the requirement in which the VBR video data is delivered to the mobile user without causing playout buffer underflow or overflows. A directional water-filling algorithm, which provides a simple and concise interpretation of the necessary optimality conditions, is identified as the optimal offline policy. Following this, two online policies are proposed for power control based on channel side information (CSI) prediction within a short time window. Dynamic programming is employed to implement the optimal offline and the initial online power control policies that minimize the transmit power consumption in the communication session. Subsequently, reinforcement learning (RL)-based approach is employed for the second online power control policy. Through the simulation results, we show that the optimal offline power control policy that minimizes the overall power consumption leads to substantial energy savings compared with the strategy of minimizing the time duration of video streaming. We also demonstrate that the RL algorithm performs better than the dynamic programming-based online grouped water-filling (GWF) strategy unless the channel is highly correlated.

In this paper, we investigate the problem of power control for streaming variable-bit-rate (VBR) videos in a device-to-device (D2D) wireless network. A VBR video traffic model that considers video frame sizes and playout buffers at the mobile users is adopted. A setup with one pair of D2D users (DUs) and one cellular user (CU) is considered and three modes, namely cellular mode, dedicated mode and reuse mode, are employed. Mode selection for the data delivery is determined and the transmit powers of the base station (BS) and device transmitter are optimized with the goal of maximizing the overall transmission rate while VBR video data can be delivered to the CU and DU without causing playout buffer underflows or overflows. A low-complexity algorithm is proposed. Through simulations with VBR video traces over fading channels, we demonstrate that video delivery with mode selection and power control achieves a better performance than just using a single mode throughout the transmission.

In this paper, wireless video transmission over full-duplex channels under total bandwidth and minimum required quality constraints is studied. In order to provide the desired performance levels to the end-users in real-time video transmissions, quality of service requirements such as statistical delay constraints are also considered. Effective capacity is used as the throughput metric in the presence of such statistical delay constraints since deterministic delay bounds are difficult to guarantee due to the time-varying nature of wireless fading channels. A communication scenario with multiple pairs of users in which different users have different delay requirements is addressed. Following characterizations from the rate-distortion theory, a logarithmic model of the quality-rate relation is used for predicting the quality of the reconstructed video in terms of the peak signal-to-noise ratio at the receiver side. Since the optimization problem is not concave or convex, the optimal bandwidth and power allocation policies that maximize the weighted sum video quality subject to total bandwidth, maximum transmission power level and minimum required quality constraints are derived by using monotonic optimization theory.

In this paper, wireless video transmission over full-duplex channels is studied. In order to provide the desired performance levels to the end-users in real-time video transmissions, quality of service (QoS) requirements such as statistical delay constraints are also considered. Effective capacity (EC) is used as the throughput metric in the presence of such statistical delay constraints since deterministic delay bounds are difficult to guarantee due to the time-varying nature of wireless fading channels. A communication scenario with a pair of users and multiple subchannels in which users can have different delay requirements is addressed. Following characterizations from the rate-distortion (R-D) theory, a logarithmic model of the quality-rate relation is used for predicting the quality of the reconstructed video in terms of the peak signal-to-noise ratio (PSNR) at the receiver side. Since the optimization problem is not concave or convex, the optimal power allocation policy that maximizes the weighted sum video quality subject to total transmission power constraint is derived by using monotonic optimization (MO) theory. The optimal scheme is compared with two suboptimal strategies.

This paper studies the performance of hierarchical modulation-based image transmission in device-to-device (D2D) cellular wireless networks under constraints on both transmit and interference power levels. Hierarchical quadrature amplitude modulation (HQAM) is considered in which high priority (HP) data is protected more than low priority (LP) data. In this setting, closed-form bit error rate (BER) expressions for HP data and LP data are derived over multiple Rayleigh fading subchannels in 3 different transmission modes. The optimal power control that minimizes weighted sum of average BERs of HP bits and LP bits or its upper bound subject to average transmit power and average interference power constraints is derived. Performance comparisons of image transmission in 3 different modes are carried out, and the proposed power control strategies are evaluated in terms of the BERs and received data quality.

This paper studies the performance of hierarchical-modulation-based image and video transmission in cognitive radio systems with imperfect channel sensing results under constraints on both transmit and interference power. Data intended for transmission is first compressed via source coding techniques and then divided into two priority classes, namely high priority (HP) data and low priority (LP) data, by taking into consideration the unequal importance of bits in the output codestream. After dividing the compressed data into packets of equal size, turbo coding is applied. Finally, the resulting packets are modulated using hierarchical quadrature amplitude modulation (HQAM). In this setting, closed-form bit error probability expressions for HP data and LP data are derived over Nakagami-m fading channels in the presence of sensing errors. Subsequently, the effects of probabilities of detection and false alarm on error rate performance of cognitive transmissions are evaluated. In addition, tradeoffs between the number of retransmissions and peak signal-to-noise ratio (PSNR) quality are analyzed numerically. Moreover, performance comparisons of multimedia transmission with conventional QAM and hierarchical QAM are carried out in terms of the received data quality and number of retransmissions.

Wireless embedded smart cameras provide significant advantages for surveillance applications, due to their mobility and flexibility in deployment. Many surveillance applications rely on data exchange and image transmission through the network. Moreover, with the widespread use of smart phones and social media, image exchange through crowdsourcing can provide invaluable information for surveillance and investigation purposes. However, transmission of images consumes significant amount of energy, and energy is a limited resource for wireless embedded devices. So far, not much attention has been paid to the energy consumption of a static or mobile node during image transmission for different scenarios. In this paper, we present a new approach for image transmission, which employs a relay node and decreases the overall energy consumption of the sender and the relay nodes. We have performed the experiments with actual wireless embedded smart cameras (CITRIC), with TelosB motes, for a static as well as a mobile scenario. We have compared the energy consumption of the proposed method with that of a traditional relay approach, and that of not using a relay node at all. Experimental results show that, with the proposed relay approach, the energy consumption of image transmission can be reduced by up to 16% in a mobile scenario.

Transmission over a half-duplex relay channel with secrecy and quality-of-service (QoS) constraints is studied. It is assumed that data is stored in buffers prior to transmission and transmitters operate with a constraint on the buffer overflow probability. Using the effective capacity formulation, secrecy throughput is derived for the half duplex two-hop fading relay system operating in the presence of an eavesdropper. The scenario without security considerations is also addressed. For both scenarios, minimum energy per bit is obtained. The impact of QoS exponents and channel correlation on the throughput is investigated via numerical analysis. Taking into account the path loss effect, the effect of the relay and eavesdropper locations on the throughput and energy efficiency is studied in a simple linear network.

Multi-camera multi-object tracking problem can be regarded as a multi-player game by adopting a game theoretical approach. In embedded vision sensor networks, energy, processing power and bandwidth are limited, and should be efficiently used. In this paper, in addition to dynamic grouping of the camera nodes, we focus on the (re)assignment of object tracking tasks by simultaneously considering energy levels, processing loads and accuracy/reliability of nodes in utility calculation. Instead of using a predetermined period to perform auctions, nodes trigger the reassignment process in an event-driven manner. Four scenarios are used for triggering reassignment, namely (i) new-object entry, (ii) object lost or exit, (iii) critical energy level or energy decrease rate, and (iv) critical target location and resolution. We also analyze the communication cost in terms of the number of messages sent between the cameras. We have performed experiments with different number of cameras and targets, and varying target trajectories and camera topology. We have computed the lifetime of the network with and without consideration of the energy levels in the task (re)assignment. We have also compared the number of messages sent with periodic reassignment and with the proposed event-driven triggering mechanism. The simulation results show a significant increase in the lifetime of the network as well as a decrease in the number of messages that are sent when the proposed approach is employed.