1,563 research outputs found
Low Cost Quality of Service Multicast Routing in High Speed Networks
Many of the services envisaged for high speed networks, such as B-ISDN/ATM, will support real-time applications with large numbers of users. Examples of these types of application range from those used by closed groups, such as private video meetings or conferences, where all participants must be known to the sender, to applications used by open groups, such as video lectures, where partcipants need not be known by the sender. These types of application will require high volumes of network resources in addition to the real-time delay constraints on data delivery. For these reasons, several multicast routing heuristics have been proposed to support both interactive and distribution multimedia services, in high speed networks. The objective of such heuristics is to minimise the multicast tree cost while maintaining a real-time bound on delay. Previous evaluation work has compared the relative average performance of some of these heuristics and concludes that they are generally efficient, although some perform better for small multicast groups and others perform better for larger groups. Firstly, we present a detailed analysis and evaluation of some of these heuristics which illustrates that in some situations their average performance is reversed; a heuristic that in general produces efficient solutions for small multicasts may sometimes produce a more efficient solution for a particular large multicast, in a specific network. Also, in a limited number of cases using Dijkstra's algorithm produces the best result. We conclude that the efficiency of a heuristic solution depends on the topology of both the network and the multicast, and that it is difficult to predict. Because of this unpredictability we propose the integration of two heuristics with Dijkstra's shortest path tree algorithm to produce a hybrid that consistently generates efficient multicast solutions for all possible multicast groups in any network. These heuristics are based on Dijkstra's algorithm which maintains acceptable time complexity for the hybrid, and they rarely produce inefficient solutions for the same network/multicast. The resulting performance attained is generally good and in the rare worst cases is that of the shortest path tree. The performance of our hybrid is supported by our evaluation results. Secondly, we examine the stability of multicast trees where multicast group membership is dynamic. We conclude that, in general, the more efficient the solution of a heuristic is, the less stable the multicast tree will be as multicast group membership changes. For this reason, while the hybrid solution we propose might be suitable for use with closed user group multicasts, which are likely to be stable, we need a different approach for open user group multicasting, where group membership may be highly volatile. We propose an extension to an existing heuristic that ensures multicast tree stability where multicast group membership is dynamic. Although this extension decreases the efficiency of the heuristics solutions, its performance is significantly better than that of the worst case, a shortest path tree. Finally, we consider how we might apply the hybrid and the extended heuristic in current and future multicast routing protocols for the Internet and for ATM Networks.
Coordinated Multicasting with Opportunistic User Selection in Multicell Wireless Systems
Physical layer multicasting with opportunistic user selection (OUS) is
examined for multicell multi-antenna wireless systems. By adopting a two-layer
encoding scheme, a rate-adaptive channel code is applied in each fading block
to enable successful decoding by a chosen subset of users (which varies over
different blocks) and an application layer erasure code is employed across
multiple blocks to ensure that every user is able to recover the message after
decoding successfully in a sufficient number of blocks. The transmit signal and
code-rate in each block determine opportunistically the subset of users that
are able to successfully decode and can be chosen to maximize the long-term
multicast efficiency. The employment of OUS not only helps avoid
rate-limitations caused by the user with the worst channel, but also helps
coordinate interference among different cells and multicast groups. In this
work, efficient algorithms are proposed for the design of the transmit
covariance matrices, the physical layer code-rates, and the target user subsets
in each block. In the single group scenario, the system parameters are
determined by maximizing the group-rate, defined as the physical layer
code-rate times the fraction of users that can successfully decode in each
block. In the multi-group scenario, the system parameters are determined by
considering a group-rate balancing optimization problem, which is solved by a
successive convex approximation (SCA) approach. To further reduce the feedback
overhead, we also consider the case where only part of the users feed back
their channel vectors in each block and propose a design based on the balancing
of the expected group-rates. In addition to SCA, a sample average approximation
technique is also introduced to handle the probabilistic terms arising in this
problem. The effectiveness of the proposed schemes is demonstrated by computer
simulations.Comment: Accepted by IEEE Transactions on Signal Processin
Multicast Multigroup Beamforming for Per-antenna Power Constrained Large-scale Arrays
Large in the number of transmit elements, multi-antenna arrays with
per-element limitations are in the focus of the present work. In this context,
physical layer multigroup multicasting under per-antenna power constrains, is
investigated herein. To address this complex optimization problem
low-complexity alternatives to semi-definite relaxation are proposed. The goal
is to optimize the per-antenna power constrained transmitter in a maximum
fairness sense, which is formulated as a non-convex quadratically constrained
quadratic problem. Therefore, the recently developed tool of feasible point
pursuit and successive convex approximation is extended to account for
practical per-antenna power constraints. Interestingly, the novel iterative
method exhibits not only superior performance in terms of approaching the
relaxed upper bound but also a significant complexity reduction, as the
dimensions of the optimization variables increase. Consequently, multicast
multigroup beamforming for large-scale array transmitters with per-antenna
dedicated amplifiers is rendered computationally efficient and accurate. A
preliminary performance evaluation in large-scale systems for which the
semi-definite relaxation constantly yields non rank-1 solutions is presented.Comment: submitted to IEEE SPAWC 2015. arXiv admin note: substantial text
overlap with arXiv:1406.755
Issues in providing a reliable multicast facility
Issues involved in point-to-multipoint communication are presented and the literature for proposed solutions and approaches surveyed. Particular attention is focused on the ideas and implementations that align with the requirements of the environment of interest. The attributes of multicast receiver groups that might lead to useful classifications, what the functionality of a management scheme should be, and how the group management module can be implemented are examined. The services that multicasting facilities can offer are presented, followed by mechanisms within the communications protocol that implements these services. The metrics of interest when evaluating a reliable multicast facility are identified and applied to four transport layer protocols that incorporate reliable multicast
Physical Layer Service Integration in 5G: Potentials and Challenges
High transmission rate and secure communication have been identified as the
key targets that need to be effectively addressed by fifth generation (5G)
wireless systems. In this context, the concept of physical-layer security
becomes attractive, as it can establish perfect security using only the
characteristics of wireless medium. Nonetheless, to further increase the
spectral efficiency, an emerging concept, termed physical-layer service
integration (PHY-SI), has been recognized as an effective means. Its basic idea
is to combine multiple coexisting services, i.e., multicast/broadcast service
and confidential service, into one integral service for one-time transmission
at the transmitter side. This article first provides a tutorial on typical
PHY-SI models. Furthermore, we propose some state-of-the-art solutions to
improve the overall performance of PHY-SI in certain important communication
scenarios. In particular, we highlight the extension of several concepts
borrowed from conventional single-service communications, such as artificial
noise (AN), eigenmode transmission etc., to the scenario of PHY-SI. These
techniques are shown to be effective in the design of reliable and robust
PHY-SI schemes. Finally, several potential research directions are identified
for future work.Comment: 12 pages, 7 figure
Issues in designing transport layer multicast facilities
Multicasting denotes a facility in a communications system for providing efficient delivery from a message's source to some well-defined set of locations using a single logical address. While modem network hardware supports multidestination delivery, first generation Transport Layer protocols (e.g., the DoD Transmission Control Protocol (TCP) (15) and ISO TP-4 (41)) did not anticipate the changes over the past decade in underlying network hardware, transmission speeds, and communication patterns that have enabled and driven the interest in reliable multicast. Much recent research has focused on integrating the underlying hardware multicast capability with the reliable services of Transport Layer protocols. Here, we explore the communication issues surrounding the design of such a reliable multicast mechanism. Approaches and solutions from the literature are discussed, and four experimental Transport Layer protocols that incorporate reliable multicast are examined
Multiuser Diversity Management for Multicast/Broadcast Services in 5G and Beyond Networks
The envisaged fifth-generation (5G) and beyond networks represent a paradigm shift for global communications, offering unprecedented breakthroughs in media service delivery with novel capabilities and use cases. Addressing the critical research verticals and challenges that characterize the International Mobile Telecommunications (IMT)-2030 framework requires a compelling mix of enabling radio access technologies (RAT) and native softwarized, disaggregated, and intelligent radio access network (RAN) conceptions. In such a context, the multicast/broadcast ser
vice (MBS) capability is an appealing feature to address the ever-growing traffic demands, disruptive multimedia services, massive connectivity, and low-latency applications.
Embracing the MBS capability as a primary component of the envisaged 5G and beyond networks comes with multiple open challenges. In this research, we contextualize and address the necessity of ensuring stringent quality of service (QoS)/quality of experience (QoE) requirements, multicasting over millimeter-wave (mmWave) and sub-Terahertz (THz) frequencies, and handling complex mobility behaviors. In the broad problem space around these three significant challenges, we focus on the specific research problems of effectively handling the trade-off between multicasting gain and multiuser diversity, along with the trade-off between optimal network performance and computational complexity.
In this research, we cover essential aspects at the intersection of MBS, radio resource management (RRM), machine learning (ML), and the Open RAN (O-RAN) framework. We characterize and address the dynamic multicast multiuser diversity through low-complexity RRM solutions aided by ML, orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) techniques in 5G MBS and beyond networks. We characterize the performance of the multicast access techniques conventional multicast scheme (CMS), subgrouping based on OMA (S-OMA), and subgrouping based on NOMA (S-NOMA). We provide conditions for their adequate selection regarding the specific network conditions (Chapter 4). Consequently,
we propose heuristic methods for the dynamic multicast access technique selection and resource allocation, taking advantage of the multiuser diversity (Chapter 5.1). Moreover, we proposed a multicasting strategy based on fixed pre-computed multiple-input multiple-output (MIMO) multi-beams and S-NOMA (Chapter 5.2). Our approach tackles specific throughput requirements for enabling extended reality (XR) applications attending multiple users and handling their spatial and channel quality diversity.
We address the computational complexity (CC) associated with the dynamic multicast RRM strategies and highlight the implications of fast variations in the reception conditions of the multicast group (MG) members. We propose a low complexity ML-based solution structured by a multicast-oriented trigger to avoid overrunning the algorithm, a K-Means clustering for group-oriented detection and splitting, and a classifier for selecting the most suitable multicast access technique (Chapter 6.1). Our proposed approaches allow addressing the trade-off between optimal network performance and CC by maximizing specific QoS parameters through non-optimal solutions, considerably reducing the CC of conventional exhaustive mechanisms. Moreover, we discuss the insertion of ML-based multicasting RRM solutions into the envisioned disaggregated O-RAN framework (Chapter 6.2.5). We
analyze specific MBS tasks and the importance of a native decentralized, softwarized, and intelligent conception.
We assess the effectiveness of our proposal under multiple numerical and link level simulations of recreated 5G MBS use cases operating in μWave and mmWave. We evaluate various network conditions, service constraints, and users’ mobility behaviors
Weighted Fair Multicast Multigroup Beamforming under Per-antenna Power Constraints
A multi-antenna transmitter that conveys independent sets of common data to
distinct groups of users is considered. This model is known as physical layer
multicasting to multiple co-channel groups. In this context, the practical
constraint of a maximum permitted power level radiated by each antenna is
addressed. The per-antenna power constrained system is optimized in a maximum
fairness sense with respect to predetermined quality of service weights. In
other words, the worst scaled user is boosted by maximizing its weighted
signal-to-interference plus noise ratio. A detailed solution to tackle the
weighted max-min fair multigroup multicast problem under per-antenna power
constraints is therefore derived. The implications of the novel constraints are
investigated via prominent applications and paradigms. What is more, robust
per-antenna constrained multigroup multicast beamforming solutions are
proposed. Finally, an extensive performance evaluation quantifies the gains of
the proposed algorithm over existing solutions and exhibits its accuracy over
per-antenna power constrained systems.Comment: Under review in IEEE Transactions in Signal Processin
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