1. Introduction In sensor networks, randomly distributed micro-nodes integrating sensors, data processing units, and communication modules form a network through self-organization. Utilizing various sensors built into the nodes, they measure thermal, infrared, sonar, radar, and seismic wave signals from their surrounding environment, thereby detecting numerous material phenomena of interest, including temperature, humidity, noise, light intensity, pressure, soil composition, and the size, speed, and direction of moving objects. While various communication methods can be employed, such as wired, wireless, infrared, and optical, short-range low-power wireless communication technology is generally considered most suitable for sensor networks, commonly referred to as Wireless Sensor Networks (WSNs). In such WSNs, each sensor node can collect environmental data, perform simple calculations, and communicate with other nodes and the outside world. The multi-node nature of sensor networks allows numerous sensors to work collaboratively for high-quality sensing and to form a fault-tolerant acquisition system. Due to these advantages, many distributed wireless sensor network applications have emerged in recent years, such as disaster relief, smart homes, and the detection and rescue of biological and chemical weapons attacks. However, as an emerging technology, establishing a well-functioning and robust wireless sensor network still faces many challenges. Moreover, due to its unique characteristics, the design methodology of wireless sensor networks differs significantly from that of existing wireless networks. For example, the dense distribution of sensor nodes in a sensor network necessitates extensive data management and processing techniques. Secondly, wireless sensor network nodes are generally deployed in areas difficult for humans to reach or access, making node maintenance a significant challenge. Furthermore, power consumption is a crucial issue. As tiny devices, wireless sensor nodes can only be equipped with limited power supplies, and in some applications, power replacement is nearly impossible. This makes the lifespan of sensor nodes heavily dependent on battery life, making reducing power consumption to extend system lifespan a primary consideration in wireless sensor network design. Many researchers in the field of wireless sensor networks are focusing on developing new power-saving protocols and algorithms, which require experimentation and verification on sensor network platforms. The following section introduces a wireless sensor network experimental platform where protocols and algorithms can be conveniently experimented with and verified. In this platform, we adopted Altera's NIOS soft-core embedded processor, a licensed general-purpose RISC CPU, meaning it is provided to designers as an IP core. It can be combined with a wide variety of peripherals, custom instructions, and hardware acceleration units to form a customized SOPC. This processor features a user-configurable L1 (Level 1) instruction and data cache. The NIOS processor also features a JTAG-based OCI (On-Chip Instrumentation) core, giving software developers a significant advantage in real-time debugging. The processor's software support is scalable to support network protocols such as APR, IP, ICMP, TCP, UDP, and Ethernet. 2 Wireless Sensor Network Platform Architecture A typical wireless sensor network structure is shown in Figure 1. Wireless sensor nodes access the network through a gateway node after multi-hop forwarding. The network's task management node manages, classifies, and processes the sensor information before sending it to the application user. Sensor nodes first collect environmental data such as sound, light, and distance, and after simple processing, transmit this data to the gateway node. Wireless sensor networks typically have two application modes: active polling mode and passive mode. Active mode requires the gateway node to actively poll each sensor node to obtain messages, while passive mode requires the gateway node to respond promptly when an event occurs at a sensor node. The data obtained by each sensor node can also be combined, which greatly improves the efficiency of the sensor network. Of course, this also requires the sensor nodes to have a certain computing power. [align=center] Figure 1 A typical sensor network structure diagram[/align] 3 System Hardware Implementation In the system architecture described in this paper, the main focus is on implementing the hardware platforms of the sensor nodes and the gateway. The hardware implementation of these two platforms is described below. 3.1 Hardware Implementation of Sensor Nodes The function of a sensor node is to collect data of interest and send the data to the gateway of each sensor node group. A sensor node mainly consists of a power module, a computing module, a storage unit, a communication module, and a sensing unit, as shown in Figure 2. [align=center] Figure 2 Composition of sensor node[/align] (1) Based on the node structure described above, we adopted the Cyclone series FPGA produced by Altera in the system. Cyclone is a low-cost, medium-density FPGA that uses 0.13μm all-copper SRAM technology, with capacities ranging from 2910 logic units to 20010 logic units and a 1.5V core. This allows it to be perfectly integrated with the NIOS soft-core embedded processor, enabling the integration of functional modules required for system design, such as processor, memory, A/D and D/A converters, into a programmable on-chip system, achieving a high degree of integration of sensor node modules. (2) The communication module of the sensor node is implemented by the TRF6901 radio frequency transceiver. The low power consumption and small size of this transceiver make it very suitable for use in wireless sensor network systems. This transceiver can operate in the 860MHz～930MHz common frequency band. The radio frequency module communicates with the NIOS soft-core processor through a serial port. The following are some features of the TRF6901 for reference: a. Low power consumption, maximum transmit current of 40mA, maximum receive current of 20mA, and maximum standby current of 4μA; b. Can use both OOK and FSK modulation methods; c. Integrated frequency synthesizer and voltage-controlled oscillator; d. Contains phase-locked loop and reference oscillator; e. Has a typical output power of 9dBm; f. Contains programmable battery detection circuit; g. With received signal strength detector; h. Has a flexible 3-wire serial interface for easy connection to microcontrollers; i. The reference oscillator frequency is programmable and fine-tunable; j. High integration and few external components. (3) Each sensor node is powered by AA batteries. 3.2 Hardware implementation of the gateway The hardware of the gateway mainly consists of a central processing unit, a storage unit, a frequency transceiver module and a GPRS communication module, as shown in Figure 3. The central processing unit of the gateway is mainly used to process the data collected from the sensor nodes and to complete some control functions. The central processing unit (CPU) is still implemented using a combination of Altera's Cyclone series FPGAs and the NIOS soft-core embedded processor. This design allows it to perform feature-rich applications at low cost and low power consumption. Furthermore, it can integrate many peripheral interfaces, including USB 2.0 and Ethernet interfaces. [align=center]Figure 3. Composition of the Gateway Node[/align] To transmit the collected data to the Internet, the gateway device is also equipped with a GPRS communication unit, mainly composed of Telit's GM862 module. Communication between this module and the NIOS processor uses AT commands, simplifying product design. It transmits the sensor-collected data to the Internet via China Mobile's existing GPRS network, allowing users to observe the sensor data using ordinary PCs and GPRS mobile terminals. The gateway also has the same RF transceiver module as the sensor node, used to receive data sent by the sensor node. 4. System Software Structure In our wireless sensor network system, the software is mainly located at the gateway and sensor nodes, and is primarily developed using assembly and C languages. The gateway software mainly processes and manages the data transmitted from the sensor nodes. It consists of GPRS communication software, RF communication software, command-line software, and task management software, as shown in Figure 4. The sensor node software mainly receives data from the sensor units and sends it to the gateway of the sensor node group. Except for the lack of GPRS communication software, its composition is the same as the gateway software. [align=center]Figure 4. Gateway Organizational Structure[/align] 5. Summary This article introduces a wireless sensor network demonstration system based on the NIOS soft core. The entire system is built on an embedded NIOS soft core processor, making full use of existing standard configuration IP cores in SOPC Builder. It has advantages such as high hardware integration, short design cycle, low power consumption through reasonable control of various components, and easy software development. Wireless sensor networks (WSNs) are an emerging communication application network whose applications can extend to all areas of human life and social activities. Therefore, WSNs will be a ubiquitous and vast network of the future, requiring various technological supports. Currently, this experimental platform has begun to be used in the laboratory. In the future, rapidly developing SOPC technology and mature communication technologies may be appropriately improved and further developed, and applied to WSNs, forming new market growth points and creating a new world for wireless communication.