Multi-channel Tracking with Different Fading Rates in an OFDM-PLNC Network

Neda

2018

Int J Communication

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Summary In this manuscript, fundamental limits of physical layer network coding with modulo‐sum mapping (to avoid of large cardinality), in terms of the number of superimposed signals that still render an acceptable probability of error, are studied. It is expected that (1) for a given bit error rate or throughput, an upper bound on the number of superimposed signals may exist and (2) if a large network is considered as a set of small subnetworks, and the proposed network code is used in each subnetwork, a significant increase in network throughput can be achieved. Answering these questions sheds light on the scalability of multiuser physical layer network coding with bit error rate or throughput constraints. Theoretical calculations, as well as simulation results, indicate the extraction of network coded signal from more than 2 (which is special case known as 2‐way relay channel) superimposed signals can be practical and lucrative.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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On scalability of physical layer network coding with modulo‐sum mapping overN‐way relay channels

Neda

2018

Int J Communication

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“…Previous studies investigated OFDM‐based CRNs where the network also benefits from network coding. Orthogonal frequency division multiplexing with PLNC also renders a powerful combination to cope with nonflat fading channels as well as symbol offset problems . The combination of MIMO, OFDM, and PLNC is an effective collection that is considered in Gacanin and Adachi .…”

Section: Introductionmentioning

confidence: 99%

“…Orthogonal frequency division multiplexing with PLNC also renders a powerful combination to cope with nonflat fading channels as well as symbol offset problems. [35][36][37][38] The combination of MIMO, OFDM, and PLNC is an effective collection that is considered in Gacanin and Adachi. 39 This paper investigates various detection methods in a TWRC structure with 2 single antenna end nodes and a multiantenna relay node.…”

Section: Introductionmentioning

confidence: 99%

Achieving maximum bit rate in a cognitive radio network with physical layer network coding

Neda

2018

Int J Communication

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Summary In this paper, the power allocation problem in a relay‐assisted cognitive radio network (CRN) is considered where the secondary users exchange information in an interweave mode on the basis of physical layer network coding. In order to enhance the capacity of CRN, using multiple‐input multiple‐output and orthogonal frequency division multiplexing has become very popular in the literature. This paper goes one step further to improve the throughput of secondary users using physical layer network coding by drawing off the transmission time. The main goal is to maximize the capacity of CRN, while keeping the total interference imposed on the primary users under a certain threshold. An optimal solution to this power allocation problem with limited relay power constraint, due to the limited budget, is derived; however, because of the high complexity of this method, an efficient suboptimal solution is also proposed.

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Using Physical Layer Network Coding to Improve NOMA System Throughput with Energy Harvesting Users

Naderi

2019 IEEE Global Communications Conference (GLOBECOM)

2019