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Related Experiment Video

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Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

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Joint Resource Optimization for Orthogonal Frequency Division Multiplexing Based Cognitive Amplify and Forward

Dong Qin¹, Tianqing Zhou²

¹School of Information Engineering, Nanchang University, Nanchang 330031, China.

Sensors (Basel, Switzerland)

|April 11, 2020

Summary

This summary is machine-generated.

This study optimizes resource allocation in cognitive relaying networks. A novel algorithm maximizes secondary network sum rates while managing interference to primary networks using power allocation and subcarrier pairing.

Keywords:

OFDM amplify and forward cognitive radio

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Area of Science:

Wireless Communications
Cognitive Radio Networks
Resource Allocation Optimization

Background:

Coexistence of secondary and primary networks in the same frequency band using Orthogonal Frequency Division Multiplexing (OFDM).
Challenges in traditional cooperative communication due to interference management constraints in cognitive relaying networks.

Purpose of the Study:

To investigate and solve two distinct resource allocation problems in cognitive relaying networks.
To maximize the sum rate of a secondary network under different power budget constraints while respecting primary network interference limits.

Main Methods:

Development of a joint optimization algorithm decomposing problems into power allocation and subcarrier pairing subproblems.
Derivation of a closed-form solution for secondary network power allocation considering primary network interference.
Determination of optimal subcarrier pairing based on the derived power allocation.

Main Results:

The proposed algorithm effectively manages interference to the primary network while optimizing secondary network performance.
Simulation results demonstrate the impact of signal-to-noise ratio (SNR), interference levels, relay position, and power ratio on the secondary network's sum rate.

Conclusions:

The joint optimization approach provides an efficient solution for resource allocation in cognitive relaying networks.
The findings offer valuable insights for designing future cognitive radio systems with improved spectral efficiency and interference mitigation.