Chetna Singhal

Joint Optimization of User-Experience and Energy-Efficiency in Wireless Multimedia Broadcast

This paper presents a novel cross-layer optimization framework to improve the quality of user experience (QoE) and energy efficiency of the heterogeneous wireless multimedia broadcast receivers. This joint optimization is achieved by grouping the users based on their device capabilities and estimated channel conditions experienced by them and broadcasting adaptive content to these groups. The adaptive multimedia content is obtained by using scalable video coding (SVC) with optimal source encoding parameters resulted from an innovative cooperative game. Energy saving at user terminals results from using a layer-aware time slicing approach in the transmission stage. A trade-off between energy saving and QoE is observed, and is incorporated in the definition of a utility function of the players in the formulated heterogeneous user composition and physical channel aware game. An adaptive modulation and coding scheme is also optimally incorporated in order to maximize the reception quality of the broadcast receivers, while maximizing the network broadcast capacity. Compared to the conventional broadcast schemes, the proposed framework shows an appreciable improvement in QoE levels for all users, while achieving higher energy-savings for the energy constrained users.

Class-Based Shared Resource Allocation for Cell-Edge Users in OFDMA Networks

In this paper, we present a new resource allocation scheme for cell-edge active users to achieve improved performance in terms of a higher system capacity and better quality-of-service (QoS) guarantee of the users, where we utilize the two-dimensional resource allocation flexibility of orthogonal frequency division multiple access (OFDMA) networks. Here, the mobile stations (MSs) at the cell-edge can maintain parallel connections with more than one base station (BS) when it is in their coverage area. A MS, before handoff to a new BS, seeks to utilize additional resources from the other BSs if the BS through which its current session is registered is not able to satisfy its requirements. The handoff procedure is termed as split handoff. The BSs participate in split handoff operation while guaranteeing that they are able to maintain QoS of the existing connections associated with them. In this study, first, we present the proposed shared resource allocation architecture and protocol functionalities in split handoff, and give a theoretical proof of concept of system capacity gain associated with the shared resource allocation approach. Then, we provide a differentiated QoS provisioning approach that accounts for the MS speed, its channel quality, as well as the loads at different BSs. Via extensive simulations in Qualnet, the benefits of the proposed class-based split handoff approach is demonstrated. The results also indicate traffic load balancing property of the proposed scheme in heavy traffic conditions.

Energy-Efficient and QoE-Aware TV Broadcast in Next-Generation Heterogeneous Networks

Future networks will comprise a large number of inter-connected heterogeneous devices that will receive ubiquitous multimedia services over integrated but diverse wireless network technologies. In this context, optimization of multimedia broadcast transmissions based on network resources and user-end constraints (price sensitivity, device display, and limited battery) is essential to ensure high QoE. This article discusses underlying challenges, and suggests hybrid system architecture and potential cross-layer adaptive unified solutions for energy-efficient and QoE-aware digital television broadcast services in future heterogeneous network environments. Experimental and architecture-level simulation studies of the cross-layer adaptive strategies demonstrate an increase in user equipment energy saving, QoE, and number of multimedia broadcast/multicast users being served.

eSMART: Energy-efficient Scalable Multimedia Broadcast for heterogeneous users

The reduction of energy consumption is a major concern in the current telecommunications environment - especially with the growth in usage of energy-hungry multimedia-centric applications on high-end mobile devices. In this context, this paper proposes eSMART, an Energy-efficient Scalable Multimedia Broadcast Transmission mechanism, that considers the energy-quality trade-off to reduce battery power consumption (increase energy saving) of heterogeneous mobile devices while maintaining acceptable perceived quality levels of received video. A real experimental test-bed has been built to analyze the impact of different multimedia scalability factors on the energy consumption of various mobile devices receiving broadcast content. Overall mobile device energy-saving is modeled using the accumulative effect of adaptive scalable video playback energy saving and time-sliced broadcast reception based radio-receivers energy saving. eSMARTs optimization framework performs user-centric adaptive encoding of scalable video that is broadcast to heterogeneous user equipments. eSMART serves more users at improved quality of experience levels and achieves up to 69% increase in mobile device energy savings as compared to a non-adaptive time-slicing scheme from the literature.

MDTC Video Transmission using Channel Aware Multipath Routing in Wireless Mesh Networks

In a mesh network, there are many paths available between two nodes depending on their location. To explore this property of path diversity, the information can be split into chunks and sent over different paths. An image or video when packetized and sent, there are chances that few packets may be corrupted in transmission. Spatial Correlation property of images and videos can be used to split an image or video frame into different descriptions so that spatial neighbors fall into different descriptions which can be sent independent of each other thus preserving the details better. Also, by inserting a recovery stage in between, we can overcome the existing errors to some extent with the help of their spatial/transformed neighbors. Hence, to achieve error resilience in wireless mesh networks by the virtue of path diversity and spatial correlation, Multiple Description Transform Coding (MDTC) was formulated for images and extended to videos. Multiple paths are selected based on channel state (packet error information). Intermediate recovery is added to increase the robustness of MDTC. The proposed scheme improves the PSNR of the received video and reduces end to end transmission delay in a wireless mesh network.

eM-SON: efficient multimedia service over self-organising Wi-Fi network.

This study presents eM-SON, an adaptive framework for providing efficient multimedia services over self-organising, hybrid Wi-Fi networks. In this reconfigurable architecture, multimedia services can be received via a Wi-Fi router, Wi-Fi hotspot, or Wi-Fi direct (i.e. device-to-device) mode. Experimental studies are performed to obtain user equipment (UE) battery discharge and QoS/QoE parameters for adaptive multimedia service (transmission, reception, and playback) over each of these Wi-Fi configurations. These experiments are conducted on different types of UEs (smartphone, tablets) with multimedia content encoded at several quality and scalability levels, and transmitted on each of the Wi-Fi configurations over varying load conditions and dynamic channel allocation. A centrally controlled framework is developed to optimise the multimedia content (adaptive transcoding) and network resource allocation (dynamic Wi-Fi configurations and channel allocation) based on the dynamic UE and network resource constraints. The proposed solution combinedly improves the QoS (throughput, number of retransmissions, and delay), QoE, and energy-efficiency performance of the UEs, while effectively serving an increased number of users in the system.

Machine learning based subjective quality estimation for video streaming over wireless networks

Now-a-days Wireless transmission is the major medium for video streaming. The standard codecs employed in video transmission removes the spatial and temporal redundancies to decrease the required bandwidth, This may decrease the perceptual quality of the video. So, it is important to develop frameworks that will measure the integrity of video just as a human does. Various objective and subjective parameters can be used to rate the quality of a video. The proposed algorithm employs machine learning (linear regression and support vector regression) to predict subjective quality of H.264 videos streamed over wireless networks from their objective scores. This method helps in evaluating Quality of user experience (QoE) without involving human efforts with an accuracy of 85.96% and 90.049% (on average) using linear regression and support vector regression, respectively.

Efficient Multimedia Broadcast for heterogeneous users in cellular networks

Efficient Multimedia Broadcast and Multicast Services (MBMS) to heterogeneous users in cellular networks imply adaptive video encoding, layered multimedia transmission, optimized transmission parameters, and dynamic broadcast area definition. This paper deals with MBMS by proposing a multi-dimensional approach for broadcast area definition, which provides an effective solution to all of the above aspects. By using multi-criteria K-means clustering, our scheme provides users with high levels of Quality-of-Experience (QoE) of multimedia services. Adaptive video encoding and allocation of radio resources (i.e., time-frequency resource blocks, and modulation and coding scheme) are performed based on user spatial distribution, channel conditions, service request, and user display capabilities. Simulation results show that our solution provides a 70% improvement in user QoE and 86% in number of served customers, as compared to an existing multimedia broadcast scheme.

ePAB: Energy-efficient, user-Preference based Adaptive multimedia Broadcast

Multimedia broadcast content reception process is energy-intensive. Use of mobile receiver devices with limited battery for such applications calls for reduced energy consumption. This paper presents ePAB - an energy-efficient user-Preference based Adaptive multimedia Broadcast scheme, that optimally clubs the user-preferences for a particular video quality profile, user device types, and the usage scenarios, for adaptive scalable video encoding of the broadcast content. User-preferences are obtained a priori via a subjective test questionnaire, that reflects the acceptance of the users towards a slightly lower video quality (good instead of excellent, and fair instead of good/excellent quality) in order to extend the receiver battery life. By incorporating the preference information in the video encoding, the proposed scheme helps achieve a higher energy saving as compared to the quality maximizing scheme aMultimedia broadcast content reception process is energy-intensive. Use of mobile receiver devices with limited battery for such applications calls for reduced energy consumption. This paper presents ePAB - an energy-efficient user-Preference based Adaptive multimedia Broadcast scheme, that optimally clubs the user-preferences for a particular video quality profile, user device types, and the usage scenarios, for adaptive scalable video encoding of the broadcast content. User-preferences are obtained a priori via a subjective test questionnaire, that reflects the acceptance of the users towards a slightly lower video quality (good instead of excellent, and fair instead of good/excellent quality) in order to extend the receiver battery life. By incorporating the preference information in the video encoding, the proposed scheme helps achieve a higher energy saving as compared to the quality maximizing scheme and an improved video reception quality as compared to the energy saving maximization scheme, while adhering to the user preference.nd an improved video reception quality as compared to the energy saving maximization scheme, while adhering to the user preference.