We propose a multicast scheme for multibeam satellite systems exploiting both the multiuser and spatial diversity inherent in this type of systems while taking into account realistic physical distributions of User Ter...
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We propose a multicast scheme for multibeam satellite systems exploiting both the multiuser and spatial diversity inherent in this type of systems while taking into account realistic physical distributions of User Terminals (UTs) over the coverage. Our proposed scheme makes use of the well-known Adaptive coding and Modulation (ACM) feature in Digital Video Broadcasting over Satellite, 2nd Generation (DVB-S2) and Extension (DVB-S2X) standards but also incorporates a set of innovative features. First, multilink reception, that is, receivers that can syntonize different frequencies and/or polarizations, together with networkcoding (NC) is used to enable decoding of signals from adjacent beams (spatial diversity). Second, efficient and fair allocation of resources is achieved through Proportionally Fair Multicast (PFM) scheduling. Our results, obtained over realistic nonuniform UTs distributions, show average system multicast throughput gains up to 88% with regard to state-of-the-art multicast schemes. Furthermore, a complete cross-layer architecture is proposed, fully compliant with the standard providing Quality of Service (QoS) guarantees.
Benefits of networkcoding towards enhancing communication quality, both in terms of robustness or data transmission rates, make it a significant candidate as a future networking technology. Conventionally, network co...
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Benefits of networkcoding towards enhancing communication quality, both in terms of robustness or data transmission rates, make it a significant candidate as a future networking technology. Conventionally, networkcoding is mostly used in wired infrastructures, where transmission errors between nodes are negligible. Capturing the provided benefits of networkcoding via straightforward extension from wired networks to wireless networks is not trivial. In addition to the challenges introduced through the wireless channel impairments, we can also capture the spatial diversity gain provided by the broadcast nature of the wireless channels. In this work, we design and implement a network-coded cooperation (NCC) system that operates in real time through the use of software-defined radio (SDR) nodes for the first time in the literature. We specifically target wireless networks. Our system is based on orthogonal frequency division multiple access (OFDMA) that provides a practical means to enable high transmission rates through the use of narrowband subcarriers. The developed testbed is composed of three source nodes, a relay node and two destination nodes. The transmission of the proposed NCC-OFDMA system is completed in two phases;the broadcast and the relaying phases. Multiplexing of source nodes' signals is achieved through OFDMA technique. In the broadcast phase, an OFDMA signal is transmitted to relay and destination nodes. In the relaying phase, the relay node first detects the OFDMA signal, generates network-coded symbols, and then transmits these symbols to destination nodes. At the end of these two phases, the destination nodes determine the source nodes' signals by using network decoders. The destination nodes make use of both the uncoded and network-coded symbols, which are received in broadcast and relaying phases, respectively. Destination nodes then perform network decoding. Through real-time bit error rate and error vector magnitude measurements, we show tha
With the rapid increase of energy consumption and environment problems, the need for green techniques and harvesting energy is emerging. networkcoding can provide the solution by the reduction of the unnecessary data...
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With the rapid increase of energy consumption and environment problems, the need for green techniques and harvesting energy is emerging. networkcoding can provide the solution by the reduction of the unnecessary data transmission and the estimated traffic patterns. It can also amplify the synergy in an energy harvesting capable cognitive radio (CR) network since the CR has the recognition and optimal decision functionalities. In this paper, we propose stochastic policy based wireless energy harvesting in green cognitive radio network. With the simulations, we show that the proposed scheme is better up to 20 % of the previous work.
BATS (BATched Sparse) codes are a class of efficient random linear network coding variation that has been studied for multihop wireless networks mostly in scenarios of a single communication flow. Towards sophisticate...
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BATS (BATched Sparse) codes are a class of efficient random linear network coding variation that has been studied for multihop wireless networks mostly in scenarios of a single communication flow. Towards sophisticated multi-flow network communications, we formulate a network utility maximization (NUM) problem that jointly optimizes the BATS code parameters of all the flows and network scheduling. The NUM problem adopts a batch-wise packet loss model that can be obtained from the network local statistics without any constraints on packet loss patterns. Moreover, the NUM problem allows a different number of recoded packets to be transmitted for different batches in a flow, which is called adaptive recoding. Due to both the probably nonconcave objective and the BATS code-related variables, the algorithms developed for the existing flow optimization problems cannot be applied directly to solve our NUM problem. We introduce a two-step algorithm to solve our NUM problem, where the first step solves the problem with nonadaptive recoding schemes, and the second step optimizes adaptive recoding hop-by-hop from upstream to downstream in each flow. We perform various numerical evaluations and simulations to verify the effectiveness and efficiency of the algorithm.
BATS codes are a class of efficient random linearnetwork codes. In this letter, BATS codes are generalized to incorporate batches of different sizes, and the corresponding belief propagation (BP) decoding performance...
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BATS codes are a class of efficient random linearnetwork codes. In this letter, BATS codes are generalized to incorporate batches of different sizes, and the corresponding belief propagation (BP) decoding performance is studied. Using a tree-based analysis, a sufficient condition is obtained such that the BP decoder can recover a given fraction of the input symbols with high probability. Some assumptions in the previous works are relaxed in our analysis so that the analytical results can be applied to more general scenarios.
If a network has an m-dimensional vector linear network coding (VLNC) solution, then it also has a VLNC solution for all dimensions multiple of m;but can a VLNC solution exists for dimensions not a multiple of m? If m...
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If a network has an m-dimensional vector linear network coding (VLNC) solution, then it also has a VLNC solution for all dimensions multiple of m;but can a VLNC solution exists for dimensions not a multiple of m? If m is the least positive integer such that a network has an m-dimensional VLNC solution, none of the networks shown in the literature has a VLNC solution for a dimension which is not a multiple of m. In this letter, we show that for any positive integer m >= 3, there exists a network which has no vector linear solution if the dimension is less than m - 1 but has a vector linear solution for all dimensions greater than or equal to m - 1.
An introduction is presented in which the editor discusses various reports within the issue on topics including mobile edge computing, power consumption for mobile devices, and optimised joint networkcoding for senso...
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An introduction is presented in which the editor discusses various reports within the issue on topics including mobile edge computing, power consumption for mobile devices, and optimised joint networkcoding for sensor network with correlated sources.
BATS codes are a class of low complexity random linearnetwork codes with high throughput. In a previous work, BATS codes were generalized to incorporate batches of different sizes, and a sufficient condition was obta...
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BATS codes are a class of low complexity random linearnetwork codes with high throughput. In a previous work, BATS codes were generalized to incorporate batches of different sizes, and a sufficient condition was obtained such that the belief propagation decoding can recover a given fraction of the input packets with high probability. In this letter, by investigating an optimization problem induced by the sufficient condition, we derive a condition such that it is optimal to use a constant batch size. This condition gives us a guideline for designing practical network protocol based on BATS codes. Moreover, we prove that this condition is always satisfied in line networks.
Threshold-linearnetworks are a common class of firing rate models that describe recurrent interactions among neurons. Unlike their linear counterparts, these networks generically possess multiple stable fixed points ...
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Threshold-linearnetworks are a common class of firing rate models that describe recurrent interactions among neurons. Unlike their linear counterparts, these networks generically possess multiple stable fixed points (steady states), making them viable candidates for memory encoding and retrieval. In this work, we characterize stable fixed points of general threshold-linearnetworks with constant external drive and discover constraints on the coexistence of fixed points involving different subsets of active neurons. In the case of symmetric networks, we prove the following antichain property: if a set of neurons is the support of a stable fixed point, then no proper subset or superset of can support a stable fixed point. Symmetric threshold-linearnetworks thus appear to be well suited for pattern completion, since the dynamics are guaranteed not to get stuck in a subset or superset of a stored pattern. We also show that for any graph G, we can construct a network whose stable fixed points correspond precisely to the maximal cliques of G. As an application, we design network decoders for place field codes and demonstrate their efficacy for error correction and pattern completion. The proofs of our main results build on the theory of permitted sets in threshold-linearnetworks, including recently developed connections to classical distance geometry.
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