Chuang Ye

Multimedia Transmission Over Cognitive Radio Channels Under Sensing Uncertainty

This paper studies the performance of hierarchical modulation-based multimedia transmission in cognitive radio (CR) systems with imperfect channel sensing results under constraints on both transmit and interference power levels. Unequal error protection (UEP) of data transmission using 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 in Nakagami-m fading channels in the presence of sensing errors. Subsequently, the optimal power control that minimizes weighted sum of average BERs of HP bits and LP bits or its upper bound subject to peak/average transmit power and average interference power constraints is derived and a low-complexity power control algorithm is proposed. Power levels are determined in three different scenarios, depending on the availability of perfect channel side information (CSI) of the transmission and interference links, statistical CSI of both links, or perfect CSI of the transmission link and imperfect CSI of the interference link. The impact of imperfect channel sensing decisions on the error rate performance of cognitive transmissions is also evaluated. In addition, tradeoffs between the number of retransmissions, the severity of fading, and peak signal-to-noise ratio (PSNR) quality are analyzed numerically. Moreover, performance comparisons of multimedia transmission with conventional quadrature amplitude modulation (QAM) and HQAM, and the proposed power control strategies are carried out in terms of the received data quality and number of retransmissions.

Image and video transmission in cognitive radio systems under sensing uncertainty

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.

Energy-aware and robust task (re)assignment in embedded smart camera networks

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.

Energy Efficient Image Transmission using Wireless Embedded Smart Cameras

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.

Multimedia transmission over device-to-device wireless links

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.

Optimal Resource Allocation for Full-Duplex Wireless Video Transmissions under Delay Constraints

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.

Image transmission over cognitive radio systems with channel and sensing uncertainty

This paper studies the performance of hierarchical modulation-based image transmission over cognitive radio systems operating with imperfect channel sensing results and also imperfect channel state information (CSI) regarding the interference link between the secondary transmitter and primary receiver. First, closed-form bit error rate (BER) expressions for high priority (HP) data and low priority (LP) data are derived. Subsequently, the optimal power control policies which minimize the weighted sum of upper bounds on average BERs of HP bits and LP bits subject to peak/average transmit power and average interference power constraints are determined under the assumption of imperfect CSI of the interference link. The effects of power levels of pilot signals used for channel estimation and the impact of imperfect channel sensing decisions on the performance of cognitive transmissions are analyzed in terms of the received image quality and number of retransmissions.

Energy efficiency in fading relay channels under secrecy and QoS constraints

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.

Uncoded image transmission in cognitive radio systems

In this paper, we consider robust uncoded image transmission in cognitive radio systems, where the secondary user initially performs channel sensing with possible sensing errors in the form of false alarms and miss detections, and then sends image data to the secondary receiver with two power levels depending on the sensing decisions (e.g., idle or busy). It is assumed that two dimensional (2-D) Discrete Cosine Transform (DCT) is applied to the image and the resulting DCT coefficients are directly transmitted through the wireless channel under sensing uncertainty. At the secondary receiver, DCT coefficients are first estimated via linear minimum mean square error (LMMSE) or MMSE estimation, then the received image is reconstructed. In this setting, the optimal power levels that minimize the mean squared error (MSE) of LMMSE estimation are obtained subject to average transmit power and average interference power constraints. Also, a low-complexity power control algorithm is proposed. The impact of imperfect sensing decisions and power constraints on the performance of uncoded image transmission in cognitive radio systems is analyzed through simulations. In addition, the performances of estimating DCT coefficient by using MMSE and LMMSE are compared.