[Paper Review] A Dynamic Spectrum Access on SDR for IEEE 802.15.4 networks

Rafik Zitouni, Laurent George+1 more|arXiv (Cornell University)|May 11, 2015

Cognitive Radio Networks and Spectrum Sensing5 references3 citations

TL;DR

This paper proposes a dynamic spectrum access (DSA) scheme for IEEE 802.15.4e wireless sensor networks using software-defined radio (SDR) based on GNU Radio and USRP. By employing energy detection-based spectrum sensing and a message-driven synchronization algorithm, the system enables secondary users to dynamically hop across 868/915 MHz and 2450 MHz bands, achieving an 80% improvement in packet success rate (PSR) compared to static frequency allocation under interference.

ABSTRACT

Our paper deals with a Dynamic Spectrum Access (DSA) and its implementation on a Software Defined Radio (SDR) for IEEE 802.15.4e Networks. The network nodes select the carrier frequency after Energy-Detection based Spectrum Sensing (SS). To ensure frequency hoping between two nodes in IEEE 802.15.4e Network, we propose a synchronization algorithm. We considerate the IEEE 802.15.4e Network is Secondary User (SU), and all other networks are Primary Users (PUs) in unlicensed 868/915 MHz and 2450 MHz bands of a Cognitive Radio (CR). However, the algorithm and the energy-sensor have been implemented over GNU Radio and Universal Software Radio Peripheral (USRP) SDR. In addition, real packet transmissions have been performed in two cases. In the first case, SU communicates in static carrier-frequency, while in the second case with the implemented DSA. For each case, PU transmitter disturbs SU, which calculates Packet Success Rate (PSR) to measure the robustness of a used DSA. The obtained PSR is improved by 80\% when the SU accomplished DSA rather than a static access.

Motivation & Objective

• To address spectrum scarcity in unlicensed ISM bands by enabling dynamic spectrum access in IEEE 802.15.4e-based wireless sensor networks.
• To implement a cognitive radio system where IEEE 802.15.4e networks operate as secondary users (SUs) in the presence of primary users (PUs) such as Wi-Fi and Bluetooth.
• To develop and validate a real-time, SDR-based DSA system using GNU Radio and USRP for dynamic carrier frequency selection.
• To evaluate the robustness of DSA under real-world interference conditions using measurable performance metrics like PSR and PRR.

Proposed method

• Implemented a multi-chain SDR architecture in GNU Radio supporting IEEE 802.15.4e (O-QPSK/BPSK), GMSK, and energy-sensing receivers.
• Used energy detection to sense spectrum occupancy across 868/915 MHz and 2450 MHz bands, selecting the channel with the lowest energy level as the active frequency.
• Designed a message-based synchronization algorithm to coordinate frequency selection between transmitter and receiver nodes in real time.
• Executed real-time packet transmissions using USRP SDR hardware, with data rates of 250 kbps (O-QPSK) and 20/40 kbps (BPSK) depending on band.
• Synchronized spectrum sensing with a 1800 ms cycle time per 3 MHz bandwidth chunk, enabling dynamic frequency reselection during transmission.
• Measured performance using PSR and PRR, with CRC checks to distinguish between correctly received and corrupted packets.

Experimental results

Research questions

• RQ1 How can dynamic spectrum access be effectively implemented in IEEE 802.15.4e-based wireless sensor networks using SDR platforms?
• RQ2 What is the impact of real-time spectrum sensing and dynamic frequency hopping on packet success rate under co-channel interference?
• RQ3 How does the synchronization mechanism between transmitter and receiver ensure reliable dynamic frequency selection in a distributed SDR environment?
• RQ4 To what extent does DSA improve robustness compared to static frequency allocation in crowded ISM bands?

Key findings

• The proposed DSA system achieved an 80% improvement in Packet Success Rate (PSR) compared to static frequency selection when operating under OFDM interference.
• Without DSA, PSR dropped to zero when the primary user (PU) signal was within 0.3 MHz of the secondary user (SU) carrier frequency due to undetected interference.
• With DSA, PSR and PRR dropped by approximately 20% at a 0.3 MHz spectral distance from the PU, primarily due to sensing and switching overhead.
• Spectrum sensing over a 1 MHz bandwidth took approximately 600 ms, contributing to transient data loss during sensing cycles.
• When switching to the 868 MHz band, the system adapted by changing modulation to BPSK, reducing data rate from 250 kbps to 20/40 kbps.
• The performance gain from DSA was contingent on system parameters such as inter-packet generation time and sensing cycle duration, which could be optimized to further improve PSR.