Providing ubiquitous connectivity to diverse device types is the key challenge for 5G and beyond 5G (B5G). Unmanned aerial vehicles (UAVs) are expected to be an important component of the upcoming wireless networks that can potentially facilitate wireless broadcast and support high rate transmissions. Compared to the communications with fixed infrastructure, UAV has salient attributes, such as flexible deployment, strong line-of-sight (LoS) connection links, and additional design degrees of freedom with the controlled mobility. In this paper, a comprehensive survey on UAV communication towards 5G/B5G wireless networks is presented. We first briefly introduce essential background and the space-air-ground integrated networks, as well as discuss related research challenges faced by the emerging integrated network architecture. We then provide an exhaustive review of various 5G techniques based on UAV platforms, which we categorize by different domains including physical layer, network layer, and joint communication, computing and caching. In addition, a great number of open research problems are outlined and identified as possible future research directions.

UAV Communications for 5G and Beyond: Recent Advances and Future Trends

Overview of the MPEG-4 Standard and Error Resilience Investigations

Many researches show that the power consumption of network devices of ICT is nearly 10% of total global consumption. While the redundant deployment of network equipment makes the network utilization is relatively low, which leads to a very low energy efficiency of networks. With the dynamic and high quality demands of users, how to improve network energy efficiency becomes a focus under the premise of ensuring network performance and customer service quality. For this reason, we propose an energy consumption model based on link loads, and use the network’s bit energy consumption parameter to measure the network energy efficiency. This paper is to minimize the network’s bit energy consumption parameter, and then we propose the energy-efficient minimum criticality routing algorithm, which includes energy efficiency routing and load balancing. To further improve network energy efficiency, this paper proposes an energy-efficient multi-constraint rerouting (E2MR2) algorithm. E2MR2 uses the energy consumption model to set up the link weight for maximum energy efficiency and exploits rerouting strategy to ensure network QoS and maximum delay constraints. The simulation uses synthetic traffic data in the real network topology to analyze the performance of our method. Simulation results that our approach is feasible and promising.

Energy-Efficient Multi-Constraint Routing Algorithm With Load Balancing for Smart City Applications

Next Generation Wireless Lans 802 11n And 802 11ac

Low-power wide area (LPWA) technologies are strongly recommended as the underlying networks for Internet of Things (IoT) applications. They offer attractive features, including wide-range coverage, long battery life, and low data rates. This paper reviews the current trends in this technology, with an emphasis on the services it provides and the challenges it faces. The industrial paradigms for LPWA implementation are presented. Compared with other work in the field, this paper focuses on the need for integration among different LPWA technologies and recommends the appropriate LPWA solutions for a wide range of IoT application and service use cases. Opportunities created by these technologies in the market are also analyzed. The latest research efforts to investigate and improve the operation of LPWA networks are also compared and classified to enable researchers to quickly get up to speed on the current status of this technology. Finally, challenges facing LPWA are identified and directions for future research are recommended.

Low Power Wide Area Networks: A Survey of Enabling Technologies, Applications and Interoperability Needs

Resource Allocation in Next-Generation Broadband Wireless Access Networks

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.

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

Device-to-device (D2D) communication is an emerging IoT technology for improved performance of cellular networks in terms of aspects like spectral efficiency, battery lifetime, coverage range. The 5G cellular network is supposed to provide a perception of 99.999% network availability. One of the approaches to obtain it is by intercell D2D communication that eliminates the issue of unavailability of bandwidth between two users connected with different base stations (BSs). The interference mitigation is a key challenge while using licensed cellular spectrum for D2D links. It is seen that the resource allocation to the D2D links is a complex problem when D2D pairs are connected with different base stations. This paper presents a dynamic Resource-Block (RB) sharing scheme between the D2D users and cellular users in a multi-cell cellular network. Here a D2D user pair plays a Repeated Game with the nearby base stations in such a way that the players share a subset of their initial allotted resource to maximize their utility. The game is played by every intercell D2D player with the base stations simultaneously. We show that the punishment period of a deviating player may be reduced by invoking an additional penalty factor for its fast adherence. In addition, we also compute the optimal number of initial orthogonal RBs that is allocated to the D2D and the cellular users. Evaluation of our proposed scheme in comparison to few well known existing techniques shows a marked improvement in throughput of the overall system.

A Resource Sharing Scheme for Intercell D2D Communication in Cellular Networks: A Repeated Game Theoretic Approach

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.

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

This paper presents an innovative multifaceted architecture, named energy-efficient framework for DTV broadcast over Wi-Fi networks (eWU-TV), that provides an energy efficient, user-centric, adaptive digital television (DTV) broadcast over Wi-Fi. To cater to the varied properties of the user equipments (UEs), the proposed framework broadcasts DTV content in the form of scalable video coded content that is adapted to suit the subscribers’ requirements. The user-centricity is in terms of UE device display size, user preferences for video quality profile based on device energy saving, and UE transmission technology support (DVB-T/H or Wi-Fi). Mathematical models on device battery discharge, quality of experience, and user preference are devised that closely approximate the results of device battery discharge experiments on DTV reception by heterogeneous devices over Wi-Fi/DVB-T, subjective video quality assessment study, and statistical survey of user preference. The proposed eWU-TV performance optimization framework is based on the developed models. The framework ensures that the adaptive scalable broadcast reception via Wi-Fi serves more number of users with higher quality of user experience and with provisions for significant device energy saving.

Chetna Singhal

Papers

Resource Allocation in Next-Generation Broadband Wireless Access Networks

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

A Resource Sharing Scheme for Intercell D2D Communication in Cellular Networks: A Repeated Game Theoretic Approach

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

eWU-TV: User-Centric Energy-Efficient Digital TV Broadcast Over Wi-Fi Networks