The paper elaborates on the technological and architectural innovations researched and developed by 5G-PPP Phase 1 projects and covering innovation areas such as 5G system design and evaluation, novel air interfaces, network management and security as well as virtualization and service deployment aspects.

HTTP adaptive streaming (HAS) has emerged as the main technology for video streaming applications. Multiple HAS video clients sharing the same wireless channel may experience different video qualities as well as different play-out buffer levels, as a result of both different video content complexities and different channel conditions. This causes unfairness in the end-user quality of experience. In this paper, we propose a quality-fair adaptive streaming solution with fair buffer (QFAS-FB) to deliver fair video quality and to achieve asymptotically fair play-out buffer levels among HAS clients competing for the same wireless resources in a long-term evolution (LTE) cell. In the QFAS-FB framework, the share of radio resources is optimized according to video content characteristics, play-out buffer levels, and channel conditions. The proposed solution is compared with the other state-of-the-art strategies, and the numerical results show that it significantly improves the quality fairness among heterogeneous HAS users, reduces the video quality variations, and improves the fairness among the user's play-out buffers.

In this paper we study the downlink of a TDD (Time Division Duplex) single cell system where the Base Station (BS) employs multiple antennas to serve the users taking into account the traffic patterns. The BS chooses each slot the users to be active, and serves them using Zero Forcing (ZF) precoding. This requires the knowledge of the users' channels which is assumed to be performed e.g. via uplink training. Due to the channel acquisition overhead, only a subset of users must be active at each timeslot (depending on traffic patterns and channel states). In this paper, we develop an active user selection strategy where the base station sets a given threshold for the channel gain of the users. Then, only the users that have their channel gain higher than the threshold send their training sequence and are then considered to be served. The base station estimates the channel states of these users and, due to channel reciprocity, uses these channel states to transmit data via ZF precoding. With appropriate signaling and threshold selection, which adapt to the queuing behavior of the users, we prove that our proposed method achieves a larger stability region than the baseline centralized policy where the BS selects the users based on channel statistics and queue lengths. The performance of the threshold-based method is illustrated via simulations, where we can observe a tradeoff between the expansion of the stability region and delay performance.

Mobile network operators are aiming at strategies to accommodate the expected huge traffic growth with limited impact on the core network load. Enhancing the mobile architecture, along with deploying content delivery networks, represent promising areas where operators are putting their efforts to reduce costs while meeting the service guarantees. In this article we present a novel mobile architecture for 5G networks which benefits from the joint design of distributed mobility management and mobile video content delivery networks. We first discuss the architectural aspects of this combination and then present our validation and performance results from a real Linux-based prototype implementation.

In this paper, the problem of feedback and active user selection in multiple-input single-output (MISO) wireless systems such that the system's stability region is as big as possible is examined. The focus is on a system in a Rayleigh fading environment where zero forcing precoding is used to serve all active users in every slot. Acquisition of the channel states is done via uplink training in time division duplexing mode by the active users. Clearly, only a subset of users can perform uplink training and the selection of this subset is a challenging and interesting problem especially in MISO systems. The stability regions of a baseline centralized scheme and two novel decentralized policies are examined analytically. In the decentralized schemes, the transmitter broadcasts periodically the queue state information and the users contend for the channel in a carrier sense multiple access-based manner with parameters based on the outdated queue state information and real-time channel state information. We show that, using infrequent signaling between the base station and the users, the decentralized policies outperform the centralized policy. In addition, a threshold-based user selection and training scheme for discrete-time contention is proposed. The results of this paper imply that, as far as stability is concerned, the users must be involved in the active user selection and feedback/training decision. This should be leveraged in future communication systems.

In HTTP adaptive streaming (HAS) applications multiple video clients sharing the same wireless channel may experience different video qualities as result of both different video content complexity and different channel conditions. This causes unfairness in the end-user video quality. In this paper, we propose a quality-fair adaptive streaming (QFAS) solution to deliver fair video quality to HAS clients competing for the same resources in an LTE cell. In the QFAS framework the share of radio resource is optimized according to video content characteristics and channel condition. The proposed solution is compared with other state-of-the-art strategies and numerical results in terms of SSIM quality metric shows that it significantly improves the quality fairness among heterogeneous HAS users.

In this paper we study the stability region of the 2-user MISO broadcast channel where the transmitter employs Zero Forcing precoding when both users are scheduled, taking into account the time overheads needed for uplink channel training. We show that, with proper signalling design, combining a decentralized policy with the baseline centralized one for user selection can increase the stability region of the system.

This paper proposes a control scheme for the quality-fair delivery of several encoded video streams to mobile users sharing a common wireless resource. Video quality fairness, as well as similar delivery delays are targeted among streams. The proposed controller is implemented within some aggregator located near the bottleneck of the network. The transmission rate among streams is adapted based on the quality of the already encoded and buffered packets in the aggregator. Encoding rate targets are evaluated by the aggregator and fed back to each remote video server (fully centralized solution), or directly evaluated by each server in a distributed way (partially distributed solution). Each encoding rate target is adjusted for each stream independently based on the corresponding buffer level or buffering delay in the aggregator. Communication delays between the servers and the aggregator are taken into account. The transmission and encoding rate control problems are studied with a control-theoretic perspective. The system is described with a multi-input multi-output model. Proportional Integral (PI) controllers are used to adjust the video quality and control the aggregator buffer levels. The system equilibrium and stability properties are studied. This provides guidelines for choosing the parameters of the PI controllers. Experimental results show the convergence of the proposed control system and demonstrate the improvement in video quality fairness compared to a classical transmission rate fair streaming solution and to a utility max-min fair approach.

In this work, we address the problem of power allocation for interfering transmitter-receiver pairs so that the probability that each queue length exceeds a specified threshold is fixed at a desired value. One application is satisfying QoS requirements in a dense cellular network. We deal with this problem using heavy traffic approximation techniques which lead to an asymptotic model of a (controlled) stochastic differential equation. The proposed power control strategy consists of allocating most of the power according to the states of the channel and a smaller fraction according to the queue lengths, for which we find a closed-form expression. We first consider a scenario where all channel realizations and queue lengths are known instantaneously to every transmitter. Then, the algorithm is extended to the case where only local SINR feedback is available and when queue length information is shared with delays among the transmitters. These models and results are also extended to the case where the transmitters are equipped with multiple antennas. Finally, the applicability in practical system settings are discussed and simulation results are provided to illustrate the performance of the proposed method.

This paper proposes an improved cross-layer control mechanism to efficiently stream videos to mobile users over an LTE network. A proxy-based filtering algorithm among scalable layers is considered to decide the number of SVC layers to transmit for each frame according to the communication conditions and to the class to which the video belongs to. The problem is cast in the context of Markov Decision Processes which allow the design of foresighted policies maximizing some long-term accumulated reward. Optimal actions to apply to the system are obtained by reinforcement learning. The proposed solution is implemented in an LTE simulation platform. Experiments show the performance of the proposed class-based layer filtering algorithm for a single video transmission and its robustness to content changes.

In this work we address the problem of channel probing in a multicarrier downlink wireless network where in order to collect CSI feedback from each user at a channel, a fraction of the available time for transmission is used. This means that the time left to transmit is getting smaller. We study the aspect of stability of such a system and we find a randomized algorithm which can guarantee an expansion of the stability region with respect to full probing and prior works. In addition, we investigate a special case of a probing scheme that does not require knowledge of the statistics of the channels and can still enlarge the stability region of the system. Simulations show the performance of the proposed scheme.

In this work we study the problem of channel state feedback and user scheduling in a single cell downlink wireless network employing multiple orthogonal parallel channels. The aspect of the system we are focusing on is stability. For user scheduling for stability as a performance measure, both the queue and channel states need to be known by the base station. However channel states can be known only via feedback from the receivers. In order to collect CQI feedback from each user at one channel, a fraction of the available time for transmission is used. This means that the time left to transmit is getting smaller. We present a joint feedback and scheduling algorithm which can guarantee an expansion of the stability region with respect to prior works. We also provide expressions regarding the distribution of the time needed to be devoted for feedback at each channel in some special cases. The proposed algorithm does not need knowledge of the statistics of the channels and traffic patterns. Simulations illustrate the operation of the proposed scheme.

In this paper we analyze the design of Generalized LDPC-staircase (GLDPC-staircase) codes, where the base code is an LDPC-Staircase code and component codes are Reed-Solomon codes. More precisely we compare two schemes: scheme A has the property that on each check node of the base code the repair symbol generated by the LDPC code is also a Reed-Solomon repair symbol. On the opposite, with scheme B for each check node the repair symbols generated by the LDPC code are Reed-Solomon source symbols. In this work we perform a behavioral analysis of the two schemes in order to determine the best one for ITerative + Reed Solomon (IT+RS) and Maximum Likelihood (ML) decoding. To that purpose we use an asymptotic analysis using Density evolution (DE) and EXtrinsic Information Transfer techniques, as well as a finite length analysis. We show that scheme A is globally the best solution since it significantly performs better than scheme B with an (IT+RS) decoding and yields similar performance with ML decoding.

This work introduces the Generalized Low Density Parity Check (GLDPC)-Staircase codes for the erasure channel, that are constructed by extending LDPC-Staircase codes through Reed Solomon (RS) codes based on “quasi” Hankel matrices. This construction has several key benefits: in addition to the LDPC-Staircase repair symbols, it adds extra-repair symbols that can be produced on demand and in large quantities, which provides small rate capabilities. Additionally, with selecting the best internal parameters of GLDPC graph and under hybrid Iterative/Reed-Solomon/Maximum Likelihood decoding, the GLDPC-Staircase codes feature a very small decoding overhead and a low error floor. These excellent erasure capabilities, close to that of ideal, MDS codes, are obtained both with large and very small objects, whereas, as a matter of comparison, LDPC codes are known to be asymptotically good. Therefore, these properties make GLDPC-Staircase codes an excellent AL-FEC solution for many situations that require erasure protection such as media streaming.

Unequal Erasure Protection (UEP) is an attractive approach to protect data flows that contain information of different priority levels. The various solutions that have been proposed can be classified into three families. The first one consists of specific, UEP-aware FEC codes, that map the information dependency within the code structure. It enables to design a specific solution, valid for a specific data flow, as in [3]. However, because this is a specific solution, its practical interest is also narrowed. In this work we focus on two additional solution families. One family implements UEP thanks to a dedicated packetization scheme, as it is the case with Priority Encoding Transmission (PET) [2], while the other family uses a dedicated signaling scheme, as is the case with the Generalized Object Encoding (GOE) [6]. These two solutions have the main benefit of being compatible with existing standardized Application Layer FEC (AL-FEC) schemes, which is a major practical benefit. Through a careful modeling of both proposals, we have demonstrated that the protection performance of both approaches are equivalent [7]. However additional key differences become apparent when considering such a practical metric as the peak memory consumption. Thanks to a modeling of the packet storage behavior at the receiver side, and by considering two major parameters, namely the channel loss probability and the permutation type, we show that the GOE scheme (without interleaver) requires a smaller memory storage than PET. This result is reversed if GOE uses a uniform interleaver.

This paper addresses the problem of efficient video streaming to mobile users. A cross-layer optimization of various parameters of the coding and transmission chain (coding parameters, buffer management, MAC-layer management) is performed to account for the time-varying nature of the characteristics of the transmitted contents and of the wireless channel. The problem is cast in the framework of Markov Decision Processes (MDP). This formalism provides efficient tools to compute a foresighted control policy maximizing some long-term discounted sum of rewards linked to the video quality received by the user. Experimental results illustrate the benefits in terms of average PSNR of this approach compared to a short-term (myopic) policy. The robustness of the proposed control policy to variations of the transmitted contents is also illustrated.

This paper proposes a quality-fair video delivery system able to transmit several encoded video streams to mobile users sharing some wireless resource. Video quality fairness, as well as similar delivery delay is targeted among streams. The proposed control system is implemented within some aggregator located near the bottleneck of the network.

In this paper, the problem of scalable video delivery over a time-varying wireless channel is considered. Packet scheduling and buffer management in both Application and Medium Access Control (MAC) layers are jointly considered. Various levels of knowledge of the state of the channel are considered. The control is performed via scalable layer filtering (some scalability layers may be dropped). In all cases, the problem is cast in the context of Markov Decision Processes which allows the design of foresighted policies maximizing some long-term reward. Without channel state observation, the control has to rely on the observation of the level of the MAC buffer only. Experimental results show that even with a lack of knowledge of the channel state, the foresighted control policy provides only a moderate loss in received video quality.

Video streaming is considered as one of the most important and challenging applications for next generation cellular networks. Current infrastructures are not prepared to deal with the increasing amount of video traffic. The current Internet, and in particular the mobile Internet, was not designed with video requirements in mind and, as a consequence, its architecture is very inefficient for handling video traffic. Enhancements are needed to cater for improved Quality of Experience (QoE) and improved reliability in a mobile network. In this paper we design a novel dynamic transport architecture for next generation mobile networks adapted to video service requirements. Its main novelty is the transport optimization of video delivery that is achieved through a QoE oriented redesign of networking mechanisms as well as the integration of Content Delivery Networks (CDN) techniques.

Statistical multiplexing aims at transmitting several variable bit rate (VBR) encoded video streams over a bandlimited channel. Rate-distortion (RD) models for the encoded streams are often used to control the video encoders. As discrepancies frequently occur between the actual RD characteristics and their models, buffers are placed at the output of each coder to facilitate regulation. In this paper, a statistical multiplexer is proposed where video coders and buffers are controlled in a closed loop. First, a predictive joint rate controller accounting for maximum distortion, fairness, and smoothness constraints is considered. Second, all buffers are controlled simultaneously to limit deviations from a reference buffer occupancy to prevent buffer under and overflow. The main idea is to update the encoding rate for each encoding unit according to the average level of the buffers, to maximize the quality of each program. Simulation results show that the proposed scheme yields a smooth and fair video quality among programs thanks to the predictive control and allows an efficient use of the available bandwidth.

The control of the trade-off between encoding rate and quality of compressed video is a challenging task. This control requires efficient rate and distortion (R-D) models, able to describe accurately the behavior of the compressed video. R-D models should account for the dependencies induced by the choice of frame-varying quantization parameters (QP). This paper proposes a dependent R-D model involving two independent regime-switching autoregressive (IRSAR) models. Experimental results show that the proposed model is able to represent accurately the distortion dependency between frames. For the part of the rate due to the texture, the model fits experimental curves reasonably well. The model has to be completed to account also for the part of the rate due to motion vectors and signalization.

The Digital Video Broadcasting Satellite services to Handhelds (DVB-SH) is a hybrid satellite/terrestrial system for the broadcasting of multimedia services to mobile receivers. To mitigate deep signal fading events occurring mainly in the land-mobile satellite channel, a Multi-Protocol-Encapsulation Inter-burst Forward Error Correction (MPE-IFEC) technique has been recently introduced. It is based on a clever organization of data and parities offering long interleaving. Two decoding modes have been proposed: the late decoding mode and the early decoding mode. In this paper, we propose to discuss and to analyse the impact of these decoding strate-gies on the channel change delay, known as the key issue of DVB-SH system. Based on an end-to-end DVB-SH network simulator, two criteria: the channel change delay and the cu-mulative freeze time, are computed by considering different MPE-IFEC parameters and typical DVB-SH propagation environments. These two criteria are sufficient to give us the subjective video quality of the newly joined channel.

This paper addresses the problem of video on demand delivery over a time-varying wireless channel. Packet scheduling and buffer management are jointly considered for scalable video transmission to adapt to the changing channel conditions. A proxy-based filtering algorithm among scalable layers is considered to maximize the decoded video quality at the receiver side while keeping a minimum playback margin. This problem is cast in the context of Markov Decision Processes which allows the design of foresighted policies maximizing some long-term reward. Experimental results illustrate the benefit of this approach compared to a shortterm policy in term of average PSNR improvement.

The DVB-SH system relies on a hybrid satellite/terrestrial infrastructure. A complementary solution using the interworking with a bi-directional path offered by cellular network is under investigation in DVB-Convergence of Broadcast and Mobile Services Group. This aims to provide good QoS of DVB-SH service anywhere anytime. Due to the strict reception conditions and the severe satellite channel propagation, many time-sliced bursts are lost impacting negatively the subjective video quality because the new link layer : inter-burst FEC, fails to recover the burst losses even with an adequate coding rate. In this paper, we propose a repair mechanism and a suitable architecture for real-time streaming service error handling. By recovering only some specific lost information of the broadcasted stream, the quality of TV service is improved.

Although many efforts focus on architectures enabling cooperation between heterogeneous access networks, these ones propose only basic functions that provide mobility for users and ignore problems that may affect the perceived QoS and the operator revenues. In this paper, we focus on TCP based applications and treat simultaneously packet loss, congestion window (Cwnd) and retransmission timeout (RTO) adaptation problems appearing during a handover between a high bitrate network and low bitrate network. We propose a simple solution called HAD function (Handover, Anchor and Dropping function) that implements multi-homing, packet buffering and Cwnd/RTO adaptation functions. HAD function applies to TCP Reno and new Reno versions and uses their inherent functioning. Simulation results show that this solution provides better QoS for users and larger revenues for operators. Key

A detector based on a network of Kalman filters (NKF) has recently been proposed for joint multiple access interference (MAI) and intersymbol interference (ISI) compensation in DS-CDMA systems (Sayadi, B. and Marcos, S., ISSSTA'02, vol.2, p.511-15, 2002; ICASSP'03, vol.5, p.37-40, 2003; Sayadi, Ph.D. thesis, Paris Sud University, 2003). It is based on a symbol state space representation of the DS-CDMA system. The NKF-based detector presents an exponential complexity in terms of the Kalman filters (Q/sup K/, where Q is the number of points in the symbol constellation and K is the number of active users in the system). We propose to linearize the number of Kalman filters used in the structure by combining a hybrid SIC/PIC structure and a reduced NKF based on a reduced state space representation of the DS-CDMA system. The proposed structure involves two steps. The first, called forward step, decodes the users in a serial approach using a SIC structure. The second, called backward step, is based on a hybrid SIC/PIC structure in order to produce better estimates of the transmitted symbols. The new resulting structure based on a reduced forward-backward NKF detector employs 2(K-1)Q Kalman filters. It exhibits better performance than the well known existing SIC-RAKE receiver, especially in channels with a large delay spread.

We investigate the problem of channel equalization in "/spl epsi/-contaminated" impulsive noise environments. We show that the equalizer can be structured into a network of Kalman filters (NKF) operating in parallel. It is based on a state space description of the communication system, the approximation of the a posteriori pdf of the plant noise (related to the transmitted symbols in our case) by a weighted sum of Gaussian (WSG) density functions, and the knowledge of the pdf of the "/spl epsi/-contaminated" noise which can be written as a sum of two Gaussians weighted by the probability of the appearance of impulsive and Gaussian noise in the observations. The useful information can be extracted from the received sample at any time, even when impulses occur, by exploiting the knowledge of the probability of appearance of the impulsive noise and its variance without using any clipping or localisation mechanism for impulses in the observations. Simulation results show that the performance of the proposed algorithm is less vulnerable to impulsive noise and is more robust than the conventional NKF algorithm based on impulse clipping.