Adaptive Streaming in P2P Live Video Systems: A Distributed Rate Control Approach

Dynamic Adaptive Streaming over HTTP (DASH) is a recently proposed standard that offers different versions of the same media content to adapt the delivery process over the Internet to dynamic bandwidth fluctuations and different user device capabilities. The peer-to-peer (P2P) paradigm for video streaming allows to leverage the cooperation among peers, guaranteeing to serve every video request with increased scalability and reduced cost. We propose to combine these two approaches in a P2P-DASH architecture, exploiting the potentiality of both. The new platform is made of several swarms, and a different DASH representation is streamed within each of them; unlike client-server DASH architectures, where each client autonomously selects which version to download according to current network conditions and to its device resources, we put forth a new rate control strategy implemented at peer site to maintain a good viewing quality to the local user and to simultaneously guarantee the successful operation of the P2P swarms. The effectiveness of the solution is demonstrated through simulation and it indicates that the P2P-DASH platform is able to warrant its users a very good performance, much more satisfying than in a conventional P2P environment where DASH is not employed. Through a comparison with a reference DASH system modeled via the Integer Linear Programming (ILP) approach, the new system is shown to outperform such reference architecture. To further validate the proposal, both in terms of robustness and scalability, system behavior is investigated in the critical condition of a flash crowd, showing that the strong upsurge of new users can be successfully revealed and gradually accommodated.Comment: 12 pages, 17 figures, this work has been submitted to the IEEE journal on selected Area in Communication

Recovery Failure Probability of Power-based NOMA on the Uplink of a 5G Cell for an Arbitrary Number of Superimposed Signals

This work puts forth an analytical approach to evaluate the recovery failure probability of power-based NOMA on the uplink of a 5G cell, the recovery failure being defined as the unfortunate event where the receiver is unable to decode even one out of the n simultaneously received signals. In the examined scenario, Successive Interference Cancellation (SIC) is considered and an arbitrary number of superimposed signals is present. For the Rayleigh fading case, the recovery failure probability is provided in closed-form, clearly outlining its dependency on the signal-to-noise ratio of the users that are simultaneously transmitting, as well as on their distance from the receiver

Fundamental Limits on the Uplink Performance of the Dynamic-Ordered SIC Receiver

Due to the rapid and widespread growth of the Internet-of-Things (IoT) paradigm, present days witness an exponential increase in the number of connected devices. In this regard, the orthogonal transmission techniques featured by conventional 4G and 5G systems can only support a limited number of simultaneously active users, due to their low spectral efficiency and poorly flexible resource allocation. To overcome such limitations, the 6G framework will include novel Next Generation Multiple Access (NGMA) solutions that will efficiently and flexibly connect a significantly larger number of devices over the same portion of spectrum. Under the NGMA umbrella, the Power-Domain Non-Orthogonal Multiple Access (PD-NOMA) technology is able to accommodate multiple users on the same frequencies by carefully assigning different power levels to the active users and employing Successive Interference Cancellation (SIC) receivers. In this work, we put forth a novel analytical approach to evaluate the performance that PD-NOMA achieves on the uplink of a single cell when a dynamic-ordered SIC receiver is considered. With respect to other existing works, the fundamental limits on the system performance are assessed analytically for an arbitrary number = of simultaneously transmitting users, and both the case of Rayleigh and lognormal-shadowed Rayleigh fading are examined. The closed-form expressions presented in this work, whose correctness and excellent accuracy are validated through Monte Carlo simulations, disclose the impact of lognormal shadowing and an increasingly larger number of active users on the PD-NOMA performance

On the Coexistence of Aperiodic and Periodic Traffic in Cellular Vehicle-to-Everything

Cellular Vehicle-to-Everything (C-V2X) communications are the key to connected and autonomous driving, and pave the way for future Intelligent Transport Systems (ITS). To support non-safety and safety critical applications in the demanding out-of-coverage scenario, the 3rd Generation Partnership Project (3GPP) has standardized the distributed C-V2X Mode 4 solution, whose behavior has been thoroughly analyzed for periodic traffic. In the current work, the problem of allocating aperiodic traffic in Mode 4 is tackled, a matter that has not been addressed before and that raises several challenging questions. A solution for serving such traffic type is put forth, and an analytical insight on the attainable performance is offered. Further, it is numerically proved that guaranteeing aperiodic flows good service levels is hard when their packets are not small sized. This holds true even for sophisticated physical layer choices and at relatively modest traffic densities, revealing that novel approaches to radio resource assignment are a necessity in Fifth Generation (5G) vehicular communications

An Effective Machine Learning (ML) Approach to Quality Assessment of Voice over IP (VoIP) Calls

This letter puts forward a supervised ML tech2 nique to determine the Quality of Experience (QoE) of VoIP calls. It takes its beginning from an investigation on VQmon, an enhanced E-model version that estimates the quality of IP-based voice calls adopting an objective approach. The current study demonstrates VQmon shortcomings via a comparison between the Mean Opinion Score (MOS) values this technique predicts and the actual average ratings collected from a subjective listening quality campaign. It proposes to deploy Ordinal Logistic Regression (OLR) for speech quality assessment, and results disclose that OLR outperforms popular ML algorithms, in accuracy and confusion matrices

Machine Learning for Disseminating Cooperative Awareness Messages in Cellular V2V Communications

This paper develops a novel Machine Learning (ML)-based strategy to distribute aperiodic Cooperative Awareness Messages (CAMs) through cellular Vehicle-to-Vehicle (V2V) communications. According to it, an ML algorithm is employed by each vehicle to forecast its future CAM generation times; then, the vehicle autonomously selects the radio resources for message broadcasting on the basis of the forecast provided by the algorithm. This action is combined with a wise analysis of the radio resources available for transmission, that identifies subchannels where collisions might occur, to avoid selecting them. Extensive simulations show that the accuracy in the prediction of the CAMs\u2019 temporal pattern is excellent. Exploiting this knowledge in the strategy for radio resource assignment, and carefully identifying idle resources, allows to outperform the legacy LTE-V2X Mode 4 in all respects

Out-of-Coverage Multi-Hop Road Safety Message Distribution via LTE-A Cellular V2V (C-V2V)

This work investigates the performance of a multi-hop scheme for the dissemination of road safety messages on highway segments, employing the recently standardized LTE-A Cellular Vehicle-to-Everything (C-V2X) technology. In order to guarantee a seamless service in areas where cellular coverage is unavailable, vehicles directly communicate over the unlicensed ITS 5.9 GHz frequency band, operating in accordance to Mode 4 of the C-V2X standard. The behavior of the proposed scheme reveals that the delivery of safety messages can successfully take place on a dedicated radio channel, as well as on a shared channel where periodic messages are broadcast at the maximum frequency foreseen by ETSI

A Comparative Study on the Quality of Narrow-Band and Wide-Band AMR VoLTE Calls

This work performs a comparative analysis of the end-to-end quality guaranteed by Voice over LTE (VoLTE), examining several millions of VoLTE calls that employ two popular speech audio codecs, namely, Adaptive Multi-Rate (AMR) and Adaptive Multi-Rate Wide Band (AMR-WB). To assess call quality, VQmon, an enhanced version of the standardized E-Model, is utilized. The study reveals to what extent AMRWB based calls are more robust against network impairments than their narrowband counterparts; it further shows that the dependence of call quality on the packet loss rate is approximately exponential for both types of codec