In IoT applications, LoRa stands out with its long distance, low power consumption, and wide coverage, becoming the preferred communication choice for scenarios such as smart meter reading, environmental monitoring, and agricultural sensing. However, with the expansion of the LoRa master-slave network and frequent data reporting, data conflict problems have become increasingly prominent. Multiple slave nodes send data to the master node at the same time, and the signals interfere with each other, causing the master node to be unable to parse, resulting in a series of problems such as data loss, retransmission, increased delay, and soaring energy consumption. Next, we will explore the root cause of data conflicts.

1. The mechanism of data conflict in LoRa master-slave mode

Based on spread spectrum modulation technology, LoRa achieves high anti-interference and sensitivity with parameters such as spreading factor (SF) and bandwidth (BW), but the characteristics of half-duplex communication and the inability to listen to the channel during transmission bury hidden dangers for data conflicts. There are two modes of master-slave interaction: master node polling and slave node active reporting.

In the master node polling mode, the master node sequentially asks the slave node whether it has data to send. The transmission is orderly but inefficient. When there are many nodes, the polling cycle is long, the real-time performance is poor and resources are wasted. The active reporting mode of the slave node is more common. The slave node directly sends data after meeting the conditions. It has strong real-time performance, but lacks global coordination. Multiple nodes are prone to send at the same time, causing conflicts.

Traditional carrier sense multiple access (CSMA) is difficult to implement in LoRa scenarios. Low-power slave nodes consume power for a long time, and are affected by the propagation characteristics of LoRa signals and the problem of hidden nodes, making it difficult to judge the channel status. Therefore, most low-power LoRa nodes use a similar pure ALOHA or time-slot ALOHA mode to "blindly send" data, which increases the frequency of conflicts.

2. Multiple impacts of data conflicts on LoRa master-slave networks

Data conflicts directly lead to data loss and trigger retransmissions, which in turn aggravate channel congestion, form a vicious cycle of conflicts and retransmissions, and greatly increase communication delays. From the derivative impact point of view, LoRa devices consume high energy for long-distance transmission, and invalid transmission and retransmission caused by conflicts seriously shorten battery life; at the same time, network capacity is limited, reducing the number of nodes that can be supported in the same area and the same channel; in key services, conflicts may cause the loss of important data such as alarms, reducing system reliability. The probability of conflict is positively correlated with the number of nodes and the frequency of data transmission. When the number of nodes increases and the transmission is frequent, the probability of conflict increases exponentially.

3. Strategies and practices for dealing with data conflicts in LoRa master-slave mode

(I) Time Division Multiple Access (TDMA): Strict time slot allocation mechanism

TDMA allocates exclusive communication time slots to slave nodes through the master node, which can theoretically eliminate conflicts, and is easy to manage and deterministic. However, this scheme has extremely high requirements for clock synchronization, is complex to implement and increases signaling overhead; the network scalability is poor, and fixed time slots are difficult to adapt to dynamic changes in nodes; resource utilization is low, idle when no data is sent, and burst data transmission is limited; master node failure can also cause the entire network to paralyze. It is suitable for industrial control scenarios with fixed nodes, stable data reporting cycles, and strict latency requirements.

(II) Improved random access (Enhanced ALOHA): Optimized disorderly access scheme

The improved random access scheme is optimized on the basis of basic ALOHA. The adaptive data rate (ADR) dynamically adjusts node parameters to shorten transmission time and reduce conflict windows; the pseudo-random backoff strategy disperses retransmission time; and the lightweight carrier sense (LCS) filters some interference. This solution is simple and easy to implement, has low requirements for clock synchronization, and supports dynamic node joining, but it cannot eliminate conflicts. It does not work well under high load, and ADR may lag behind in complex environments. It is suitable for small and medium-sized smart home scenarios with strong node mobility, random data reporting, and cost sensitivity.

(III) Hybrid solution: a comprehensive strategy of integrating advantages

The hybrid solution combines the advantages of TDMA and random access, and divides the communication cycle into "beacon frames" and "contention access period (CAP)". Beacon frames are used for synchronization and time slot allocation. Nodes use the improved ALOHA mechanism to send small data or requests in the CAP. Data that requires large-scale transmission or is sensitive to delay can apply for TDMA time slots. This solution has both determinism and flexibility, and is suitable for a variety of services, but the protocol is highly complex, and the design, implementation and debugging are difficult, and the signaling overhead is also increased accordingly. It is suitable for medium and large-scale smart city scenarios with complex business types and high network performance requirements.

4. Key points for solution selection and optimization practice

Selection of conflict resolution solutions requires comprehensive consideration of factors such as network scale, data characteristics, latency requirements, power consumption limits, cost and complexity. When the network scale is large and the node density is high, pay attention to the solution's support for network capacity; periodic data is suitable for TDMA, and bursty data is adapted to random access solutions; TDMA or hybrid solution dedicated time slots are strictly selected for latency requirements; power consumption is highly constrained, focusing on energy consumption optimization; and taking both cost and complexity into account.

In actual optimization, fine-tune parameters such as SF, BW, CR, and TP to shorten data packet transmission time; reasonably plan channels and spreading factors to isolate conflict domains; avoid nodes waking up and reporting at the same time through load balancing; and weigh the use of explicit ACK and implicit ACK as needed.

5. Conclusion: Looking to the future

The data conflict problem of LoRa master-slave mode originates from the physical layer characteristics and the limitations of master-slave interaction. TDMA, Enhanced ALOHA and hybrid solutions have their own advantages and disadvantages, and need to be selected in combination with the scenario. With the advancement of AI-based MAC protocol research and the evolution of LoRaWAN protocol, it is expected that the conflict problem will be better solved in the future. However, no matter how the technology develops, a deep understanding of the principles and precise practice are still the cornerstones of building a reliable LoRa network.