Jianjun Wu

Bio: Jianjun Wu is an academic researcher from Huawei. The author has contributed to research in topics: Computer science & Wireless network. The author has an hindex of 2, co-authored 2 publications receiving 220 citations.

Quality-driven cross-layer optimized video delivery over LTE

Abstract: 3GPP long term evolution is one of the major steps in mobile communication to enhance the user experience for next-generation mobile broadband networks. In LTE, orthogonal frequency-division multiple access is adopted in the downlink of its E-UTRA air interface. Although cross-layer techniques have been widely adopted in literature for dynamic resource allocation to maximize data rate in OFDMA wireless networks, application-oriented quality of service for video delivery, such as delay constraint and video distortion, have been largely ignored. However, for wireless video delivery in LTE, especially delay-bounded real-time video streaming, higher data rate could lead to higher packet loss rate, thus degrading the user-perceived video quality. In this article we present a new QoS-aware LTE OFDMA scheduling algorithm for wireless real-time video delivery over the downlink of LTE cellular networks to achieve the best user-perceived video quality under the given application delay constraint. In the proposed approach, system throughput, application QoS constraints, and scheduling fairness are jointly integrated into a cross-layer design framework to dynamically perform radio resource allocation for multiple users, and to effectively choose the optimal system parameters such as modulation and coding scheme and video encoding parameters to adapt to the varying channel quality of each resource block. Experimental results have shown significant performance enhancement of the proposed system.

A 25 Gb/s(/km 2 ) urban wireless network beyond IMT-advanced

Abstract: In this article we present a survey on the technical challenges of future radio access networks beyond LTE-Advanced, which could offer very high average area throughput to support a huge demand for data traffic and high user density with energy-efficient operation. We highlight various potential enabling technologies and architectures to support the aggressive goal of average area throughput 25 Gb/s/km2 in beyond IMT-Advanced systems. Specifically, we discuss the challenges and solutions from the controlling/ processing perspective, the radio resource management perspective, and the physical layer perspective for dense urban cell deployment. Using various advanced technologies such as interference mitigation techniques, MIMO, and cooperative communications as well as cross-layer self-organizing networks, we show that future urban wireless networks could potentially offer high-quality mobile services and offer an experience similar to the wired Internet.

Intelligence-Endogenous Networks: Innovative Network Paradigm for 6G

Abstract: Feature applications envisioned in the 6G era, represented by holographic communication, full-sensing communication, intelligent transportation, and intelligent manufacturing in terms of virtual and physical integration, immersion, contextualization, and personalization, have placed high demands on the intelligentization of 6G networks. The current network operating mechanism based on rule-based algorithms is limited by rigid preset rules. It is difficult to adapt dynamically to constantly changing user needs and network environments. In order to enable the network to effectively accumulate and independently utilize the operating experience and realize the independent iterative evolution of network operation, management, and control capabilities, this article proposes the concept of the intelligence-endogenous network (IEN). The IEN aims to introduce knowledge graph and artificial intelligence technologies into networks to characterize, construct, learn, and apply the network's multidimensional subjective and objective knowledge. Based on the learned knowledge, an IEN can realize stereo perception, decision deduction, and dynamic adjustment, so the network can change as it needs for whatever new services we want. The article introduces the basic concepts, goals, and meanings of the IEN, together with its key principles and technologies, and illustrates how it innovatively responds to the current network's multifaceted challenges with an intuitive use case.

Research and realization of gigabit Ethernet frame slicing

Abstract: Aiming at solving the problem that RS code cannot be applied in gigabit Ethernet transmission due to the length of Ethernet random frame, a module for slicing Ethernet frame is designed in this paper. The designed slicing module can slice Ethernet frames of any length to adapt to RS codes of different lengths, and the receiver module can find the slicing frame header again and restore the slicing frame to Ethernet frame. The experimental results show that the designed transmitter and receiver can slice and restore Ethernet frames at Gigabit rate, and there are no transmission error frames, which meets the design requirements.

Joint Precoding and Multivariate Backhaul Compression for the Downlink of Cloud Radio Access Networks

Abstract: This work studies the joint design of precoding and backhaul compression strategies for the downlink of cloud radio access networks. In these systems, a central encoder is connected to multiple multi-antenna base stations (BSs) via finite-capacity backhaul links. At the central encoder, precoding is followed by compression in order to produce the rate-limited bit streams delivered to each BS over the corresponding backhaul link. In current state-of-the-art approaches, the signals intended for different BSs are compressed independently. In contrast, this work proposes to leverage joint compression, also referred to as multivariate compression, of the signals of different BSs in order to better control the effect of the additive quantization noises at the mobile stations (MSs). The problem of maximizing the weighted sum-rate with respect to both the precoding matrix and the joint correlation matrix of the quantization noises is formulated subject to power and backhaul capacity constraints. An iterative algorithm is proposed that achieves a stationary point of the problem. Moreover, in order to enable the practical implementation of multivariate compression across BSs, a novel architecture is proposed based on successive steps of minimum mean-squared error (MMSE) estimation and per-BS compression. Robust design with respect to imperfect channel state information is also discussed. From numerical results, it is confirmed that the proposed joint precoding and compression strategy outperforms conventional approaches based on the separate design of precoding and compression or independent compression across the BSs.

Two-Level Downlink Scheduling for Real-Time Multimedia Services in LTE Networks

Abstract: Long-term evolution represents an emerging technology that promises a broadband and ubiquitous Internet access. But several aspects have to be considered for providing effective multimedia services to mobile users. In particular, in this work, we consider the design of a quality-of-service (QoS) aware packet scheduler for real-time downlink communications. To this aim, a novel two-level scheduling algorithm is conceived. The upper level exploits an innovative approach based on discrete-time linear control theory. Instead, at the lower level, a proportional fair scheduler has been properly tailored to our purposes. The performance and the complexity of the proposed scheme have been evaluated both theoretically and by using simulations. A comparison with recently proposed scheduling strategies has been also presented, considering several network conditions and real-time multimedia flows. Particular attention has been devoted to the evaluation of the quality-of-experience (QoE) provided to end users. Results have clearly shown that the proposed approach is able to greatly outperform the existing ones especially in the presence of real-time video flows.

Method and apparatus for distributing content in a communication network

Abstract: Aspects of the subject disclosure may include, for example, a system for receiving decoded satellite signals, obtaining media channels from the decoded satellite signals, selecting a portion of the media channels for distribution to a plurality of media processors, encoding the portion of the media channels selected according to a satellite distribution protocol, such as a protocol that facilitates satellite switching, to generate satellite encoded content, formatting the satellite encoded content according to a transport protocol to generate formatted content, and providing the formatted content for distribution to the plurality of media processors via a communication network, such as a single wire communication network or other network. Other embodiments are disclosed.

Robust and Efficient Distributed Compression for Cloud Radio Access Networks

Abstract: This paper studies distributed compression for the uplink of a cloud radio access network where multiple multiantenna base stations (BSs) are connected to a central unit, which is also referred to as a cloud decoder, via capacity-constrained backhaul links. Since the signals received at different BSs are correlated, distributed source coding strategies are potentially beneficial. However, they require each BS to have information about the joint statistics of the received signals across the BSs, and they are generally sensitive to uncertainties regarding such information. Motivated by this observation, a robust compression method is proposed to cope with uncertainties on the correlation of the received signals. The problem is formulated using a deterministic worst case approach, and an algorithm is proposed that achieves a stationary point for the problem. Then, BS selection is addressed with the aim of reducing the number of active BSs, thus enhancing the energy efficiency of the network. An optimization problem is formulated in which compression and BS selection are performed jointly by introducing a sparsity-inducing term into the objective function. An iterative algorithm is proposed that is shown to converge to a locally optimal point. From numerical results, it is observed that the proposed robust compression scheme compensates for a large fraction of the performance loss induced by the imperfect statistical information. Moreover, the proposed BS selection algorithm is seen to perform close to the more complex exhaustive search solution.

Control-Data Separation Architecture for Cellular Radio Access Networks: A Survey and Outlook

Abstract: Conventional cellular systems are designed to ensure ubiquitous coverage with an always present wireless channel irrespective of the spatial and temporal demand of service. This approach raises several problems due to the tight coupling between network and data access points, as well as the paradigm shift towards data-oriented services, heterogeneous deployments and network densification. A logical separation between control and data planes is seen as a promising solution that could overcome these issues, by providing data services under the umbrella of a coverage layer. This article presents a holistic survey of existing literature on the control-data separation architecture (CDSA) for cellular radio access networks. As a starting point, we discuss the fundamentals, concepts, and general structure of the CDSA. Then, we point out limitations of the conventional architecture in futuristic deployment scenarios. In addition, we present and critically discuss the work that has been done to investigate potential benefits of the CDSA, as well as its technical challenges and enabling technologies. Finally, an overview of standardisation proposals related to this research vision is provided.