GFDM-based wireless energy-carrying network uplink and downlink resource joint allocation method

A wireless energy carrying and link resource technology, applied in the field of resource joint allocation optimization algorithm

Active Publication Date: 2021-04-23
HANGZHOU DIANZI UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Simultaneous Wireless Information and Power Transfer (SWIPT) provides a new method of energy harvesting for energy-constrained network nodes, and realizes the simultaneous transmission of information and energy. However, there is a trade-off between information transmission and energy harvesting.

Method used

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  • GFDM-based wireless energy-carrying network uplink and downlink resource joint allocation method
  • GFDM-based wireless energy-carrying network uplink and downlink resource joint allocation method
  • GFDM-based wireless energy-carrying network uplink and downlink resource joint allocation method

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Embodiment Construction

[0063] figure 1 It is the SWIPT network scenario diagram based on GFDM. The scenario consists of a base station (Base Station, BS) and multiple SWIPT users. The SWIPT user has an energy harvesting function, and the energy used for the uplink transmission signal only comes from the signal transmitted by the base station. At the same time, the base station is equipped with N antennas, while other nodes in the network have only a single antenna. It is assumed that the communication links between nodes are subject to Rayleigh fading, and each node is fully aware of all channel state information. In the downlink, each user adopts a power division based receiver structure. in, figure 1 (a) is the downlink antenna selection scheme diagram. A downlink transmission antenna selection (Transmission Antenna Selection, TAS) scheme is implemented at the BS. An optimal antenna is selected for a SWIPT user through the TAS scheme. Each antenna can only be assigned to one SWIPT user, tha...

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Abstract

The invention discloses a GFDM-based wireless energy-carrying network uplink and downlink resource joint allocation method. Each user performs information decoding and energy collection on a received signal by adopting a power division receiver structure in a downlink, and then uses the collected energy for uplink information transmission. The weighted reachable sum rate of the uplink and the downlink is maximized under the condition of meeting the constraint of energy collection and total transmitting power by allocating GFDM subcarriers and subsymbols of the uplink and the downlink and allocating power allocation and power division factors. In order to solve the non-convex optimization problem, a Lagrange duality method, a sub-gradient method and a greedy algorithm are respectively adopted to solve the joint optimization of uplink and downlink power distribution and power segmentation factors. The invention is superior to a fixed subcarrier distribution algorithm. According to the invention, multi-resource optimal allocation of uplink and downlink subcarriers, subsymbols, power and power segmentation factors of the wireless energy-carrying network based on GFDM is effectively realized.

Description

technical field [0001] The invention belongs to the technical field of information and communication engineering, and proposes a joint resource allocation optimization algorithm for uplink and downlink in a wireless power-carrying communication (SWIPT) network based on generalized frequency division multiplexing (GFDM). First, for the downlink, each SWIPT user uses a power division (PS) receiver structure to complete information decoding (ID) and energy harvesting (EH) after receiving information from the base station, and then uses the collected energy for uplink information transmission . Through the allocation of uplink and downlink GFDM subcarriers and subsymbols, power allocation and power division factor allocation, the weighted reachable sum rate of uplink and downlink is maximized under the constraints of collecting energy and total transmission power. In order to solve this non-convex optimization problem, Lagrangian dual method, subgradient method and greedy algorit...

Claims

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Application Information

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IPC IPC(8): H04W72/04
CPCH04W72/0473H04W72/0453H04W72/53H04W72/21H04W72/23Y02D30/70
Inventor 许晓荣孙明杭赵彬王玉军
Owner HANGZHOU DIANZI UNIV
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