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A Simplified Analog Implementation of Cyclic Shift Chirp Encoding and Decoding for LoRa Communications
(2026-06-01)
Saelim, Nopparut
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Tuwanut, Panwit
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Pornavalai, Chotipat
Currently, LoRa wireless communication technology has become widely adopted in IoT systems due to its long-range capability and low power consumption. However, LoRa is a technology developed by Semtech, which does not disclose the details of the Cyclic Shift Chirp encoding process, a core component of LoRa signals. This lack of transparency prevents users from accessing the physical-layer structure of the signal or freely customizing key parameters such as bandwidth and spreading factor. Although such customization can enhance system flexibility, there is currently no officially disclosed method to achieve it. This research proposes a Cyclic Shift Chirp encoder/decoder circuit built from basic analog components, including adders, subtractors, comparators, and ramp generators, based on a Pulse Width Modulation (PWM) principle. This approach enables researchers and developers to generate LoRa-like signals independently and customize various parameters without introducing limitations. Moreover, the proposed circuit is simple, low-cost, and easy to understand, making it suitable for advanced research, educational experiments, and the design of communication systems that require high flexibility at the LoRa PHY layer.
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EORL: Energy Optimization via Reinforcement Learning in Software-Defined Wireless Sensor Networks
(2024-01-01)
Boonlert, Arnut
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Pornavalai, Chotipat
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Tuwanut, Panwit
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Tanessakulwattana, Sarayoot
A wireless sensor network is a collection of sensors placed in a particular area to collect and transmit data to the base station or sink. They usually have batteries as the primary power sources. If they work for a long time, their energy will be exhausted. Replacing the battery may not be cost-effective compared to developing an algorithm that optimizes energy efficiency to extend the network lifetime. This work optimizes the energy consumption of wireless sensor networks by adaptively selecting an optimal routing path in a Software-defined Wireless Sensor Networks (SDWSN) environment. A concept of the energy balance among nodes according to the current network status by the SDWSN controller using Reinforcement Learning (RL) is introduced. We propose energy optimization via reinforcement learning (EORL) for SDWSN using a minimum energy reward function and state design that considers energy consumption. The EORL algorithm then identifies the node that requires attention and selects the most energy-efficient path for that node. The performance of the EORL shows that it has a more extended network lifetime compared with other RL solutions.
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A Novel Precomputed Optimal Procrastination Time Interval for Re-Clustering to Maximize Operation Time of Wireless Sensor Networks
(2023-09-01)
Pornavalai, Chotipat
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Tanessakulwattana, Sarayoot
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Chakraborty, Goutam
In wireless sensor networks, the energy consumption of sensors is not uniform over the whole region of deployment. The uneven energy usage occurs because some sensors have to transmit data to farther distances or have to transmit more data packets than others. This leads to a shorter duration of operation because some sensors' energy will deplete fast creating holes in the network. To alleviate this problem, we proposed an algorithm we named Procrastinated Clustering and Multi-Hop Routing (PCMR). To prolong the operation, it will optimally assign sensors with different precomputed procrastination periods to schedule the clustering and routing processes. In PCMR, sensors' clustering and routing intervals depend on their locations in the network with respect to the sink. The algorithm could reduce and balance energy consumption for sensors distributed over a wide area. Procrastination periods are precomputed off-line before deployment. Therefore, it is easy to implement and is efficient, even for a large network for which real-time reorganization would involve transmitting a large number of signaling packets. The results from simulations show that the proposed PCMR algorithm could balance energy usage among sensors, and prolong the network lifetime compared to existing works based on techniques such as adjusting cluster size and/or multi-path transmission.
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A Practical Circuit of Cyclic Chirp Spread Spectrum Modulation for Long Range Communication
(2022-01-01)
Sinchai, Ananta
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Saelim, Nopparut
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Pornavalai, Chotipat
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Wardkein, Paramote
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Tuwanut, Panwit
Various technologies have been utilized in long range communication to satisfy increasing usage of the internet of things in a wide large area. Recently, a modulating technique called cyclic chirp spread spectrum (CSS) modulation has attracted attention due to its low power usage and long-range coverage. However, a cyclic CSS circuit is complex to build. Hence, the objective of the work is to propose a practical circuit of cyclic CSS modulation. The proposed circuit is designed to complicated-free creation. To prove that the presented circuit is pragmatic, a simulation test is performed. The simulation results have illustrated that the designed circuit well generates a chirp modulating signal. Also, the proposed circuit is flexibly configurable.

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