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Energy Efficiency of a Decode-and-Forward Multiple-Relay Network with Rate Adaptive LDPC Codes
Bushra Bashir Chaoudhry1, Syed Ali Hassan2, Joachim Speidel3
1Department of Telecommunications, University of Stuttgart, 70569 Stuttgart, Germany. bushra.bashir@fjwu.edu.pk.
Sensors (Basel, Switzerland)
|November 7, 2019
Summary
Cooperative transmission (CT) enhances Internet of Things (IoT) networks using multiple relays and channel coding. This study optimizes power allocation for energy efficiency, balancing complexity, delay, and bit error rate (BER).
Area of Science:
- Wireless Communication
- Information Theory
- Network Engineering
Background:
- Internet of Things (IoT) networks face challenges with hardware-limited devices.
- Cooperative Transmission (CT) offers array and diversity gains for improved performance.
- Decode-and-Forward (DF) relaying is crucial for multi-hop networks.
Purpose of the Study:
- To investigate a channel coding aided DF relaying network for IoT.
- To optimize power allocation for energy efficiency under Quality-of-Service (QoS) constraints.
- To analyze the trade-offs between system complexity, delay, and Bit Error Rate (BER) using Low Density Parity Check (LDPC) codes.
Main Methods:
- Utilizing Low Density Parity Check (LDPC) codes for forward error correction (FEC) at source and relays.
- Investigating both fixed and variable code rates for spectral and energy efficiency.
- Developing an optimal power allocation scheme for energy efficiency.
Main Results:
- Simulation results demonstrate the effectiveness of the proposed cooperative transmission scheme.
- Decoupled code rates on different hops introduce a trade-off between system complexity, transmission delay, and BER.
- The study quantifies performance gains compared to conventional methods.
Conclusions:
- Cooperative transmission with LDPC codes is a viable technology for enhancing IoT networks.
- Optimal power allocation is key to achieving energy efficiency in cooperative systems.
- Careful selection of code rates is necessary to manage system complexity, delay, and error performance.
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