In this paper, we investigate the throughput capacity of large-scale wireless networks, in which three network-assisted coding schemes are considered: (1) multi-point-to-point coding (MPPC);(2) MPPC based network codi...
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In this paper, we investigate the throughput capacity of large-scale wireless networks, in which three network-assisted coding schemes are considered: (1) multi-point-to-point coding (MPPC);(2) MPPC based network coding (NC);and (3) MPPC based physical-layer network coding (PLNC). This study is based on the generalized physical model, in which the transmission rate depends on the signal to noise and interference ratio (SINR). Such a model has not been used to analyze the behaviors of large-scale wireless networks with the aforementioned coding schemes. To understand the capacity gains of these schemes, we develop constructive lower bounds for one-dimensional (1D) and two-dimensional (2D) networks with size factor w, in which we construct novel wireless highway systems. This study shows that, compared to point-to-point coding (PPC), MPPC can improve the scaling law of network capacity when w exceeds a certain scale. In addition, this study reveals that MPPC based NC and PLNC can improve the capacity by constant factors. Specifically, NC can always obtain a gain of 2 in both 1D and 2D networks. On the other hand, the gain of PLNC can be larger than 2 in 1D networks, and can be up to 2 in 2D networks, depending on w, transmission power, noise, and path-loss of propagation.
作者：
Cai, NingXidian Univ
State Key Lab Integrated Serv Networks ISN Xian 710071 Peoples R China
In this work we extend localized error correction codes introduced by L. A. Bassalygo et al from point-to-point coding to non-coherent network coding. We have a lower bound and an upper bound of the capacity, which ar...
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ISBN:
(纸本)9781457705953
In this work we extend localized error correction codes introduced by L. A. Bassalygo et al from point-to-point coding to non-coherent network coding. We have a lower bound and an upper bound of the capacity, which are tight when the sum of two times of the dimension of the codewords and the dimension of error configurations does not exceed the dimension of the ground space.
Gastpar and Vetterli named the ad hoc networks with one randomly selected source-destination pair as relay networks, and they suggested using arbitrary network coding in order to increase the overall efficiency. Here,...
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Gastpar and Vetterli named the ad hoc networks with one randomly selected source-destination pair as relay networks, and they suggested using arbitrary network coding in order to increase the overall efficiency. Here, the relay network is investigated with two relays, no interference and a new achievable rate is obtained using a new network coding (decode-and-broadcast). The obtained achievable rate (i) gives the lower bound for general relay channel, obtained by Cover and El Gamal, but with a slight difference owing to no interference assumption at the receiver, (ii) includes the one relay rates of a two-level relay channel studied by Gupta and Kumar using point-to-point coding, (iii) includes the rates of two-relay Aref network and other special two-relay networks, (iv) meets the max-flow min-cut upper bound under certain additional assumptions resulting in certain capacity theorems that include the related previous capacities, (v) is validated by its consistency with previous results relevant to special cases of broadcast channels.
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