Scheduling for Network-Coded Multicast

Traskov, Danail; Heindlmaier, Michael; Médard, Muriel; Koetter, R.

doi:10.1109/tnet.2011.2180736

Cited by 40 publications

(47 citation statements)

References 18 publications

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“…The problem of finding the optimal scheme to manage the data flows over such noiseless networks is in general open. However, there exist many heuristic (and thus suboptimal in general) methods, see [11] for example, for constructing a valid inner bound.…”

Section: V: Construct An Inner Bound For the Resulting Noiseless Networkmentioning

confidence: 99%

Lower bounding models for wireless networks

Médard

Xiao

et al. 2013

2013 IEEE International Symposium on Information Theory

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Abstract-Motivated by the framework of network equivalence theory [1], [2], we present capacity lower bounding models for wireless networks by construction of noiseless networks which can be used to calculate an inner bound for the corresponding wireless network. We first extend the "one-shot" lower bounding model [6] to many-user scenarios, and then propose a two-step update of the one-shot models to incorporate the broadcast nature of wireless transmission. The main advantage of the proposed lower bounding method is its simplicity and the fact that it can be easily extended to larger networks. We demonstrate by examples that the resulting lower bounds can even approach the capacity in some setups.

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Section: V: Construct An Inner Bound For the Resulting Noiseless Networkmentioning

confidence: 99%

Lower bounding models for wireless networks

Médard

Xiao

et al. 2013

2013 IEEE International Symposium on Information Theory

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“…The problem of finding the optimal scheme to manage the data flows over such noiseless networks is in general open. However, there exist many heuristic (and thus suboptimal in general) methods, see [42] for example, for constructing a valid inner bound.…”

Section: Step Iii: Lower Bounding Models For Decoupled Macsmentioning

confidence: 99%

Scalable Capacity Bounding Models for Wireless Networks

Médard

Xiao

et al. 2016

IEEE Trans. Inform. Theory

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Abstract-The framework of network equivalence theory developed by Koetter et al. introduces a notion of channel emulation to construct noiseless networks as upper (resp. lower) bounding models, which can be used to calculate the outer (resp. inner) bounds for the capacity region of the original noisy network. Based on the network equivalence framework, this paper presents scalable upper and lower bounding models for wireless networks with potentially many nodes. A channel decoupling method is proposed to decompose wireless networks into decoupled multiple-access channels (MACs) and broadcast channels (BCs). The upper bounding model, consisting of only point-to-point bit pipes, is constructed by firstly extending the "one-shot" upper bounding models developed by Calmon et al. and then integrating them with network equivalence tools. The lower bounding model, consisting of both point-to-point and point-topoints bit pipes, is constructed based on a two-step update of the lower bounding models to incorporate the broadcast nature of wireless transmission. The main advantages of the proposed methods are their simplicity and the fact that they can be extended easily to large networks with a complexity that grows linearly with the number of nodes. It is demonstrated that the resulting upper and lower bounds can approach the capacity in some setups.

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“…Multiple applications of network coding have been thoroughly evaluated, including those in multi-hop wireless networks [26], [27], wireless cooperative networks [28], multi-way relay networks [29], [30], and delay-tolerant networks [31], [32], at the physical layer [33] (also known as analog network coding) and upper layers [34], in real-time broadcasting systems [35] and storage area networks [36], as well as many other systems. Insightful conclusions on coding scalability have also been made [37] and effects of multi-packet reception have been studied [38], as well as challenges of joint network-channel coding [39].…”

Section: B Benefits Of Coupling D2d With Network Codingmentioning

confidence: 99%

Understanding Practical Limitations of Network Coding for Assisted Proximate Communication

Pyattaev

Galinina

Andreev

et al. 2015

IEEE J. Select. Areas Commun.

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In next-generation wireless networks, device-todevice (D2D) communication represents a feasible way for mobile users to offload their cellular traffic demand without extra costs for deploying additional infrastructure from the network operators. Cellular (e.g., 3GPP LTE) network assistance can automate user/service discovery and connection establishment procedures, as well as enable secure D2D connectivity between proximate users. Currently, assisted direct connectivity is only available in the form of unlicensed-band protocols (e.g., WiFiDirect), which motivates research on understanding its practical limitations with realistic distributions of users and content. Whereas there are concerns that D2D communication alone may not be efficient due to limited content availability, in this paper we advocate the use of network coding to upgrade assisted proximate communication and make it realize its full potential. In particular, we demonstrate that even simpler network coding techniques are capable to significantly improve the degrees of content availability for communicating users and thus enhance offloading performance under realistic constraints. Inspired by the recent popularity of wireless content distribution systems over D2D caches, we contribute a practical methodology for assisted data caching and distribution, mindful of the state-of-the-art D2D technology.

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Scheduling for Network-Coded Multicast

Cited by 40 publications

References 18 publications

Lower bounding models for wireless networks

Lower bounding models for wireless networks

Scalable Capacity Bounding Models for Wireless Networks

Understanding Practical Limitations of Network Coding for Assisted Proximate Communication

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