IRS Deployment for Highly Time Sensitive Short Packet Communications: Distributed or Centralized Deployment?

ZHANG Yangyi; GUAN Xinrong; YANG Weiwei; CAO Kuo; WANG Meng; CAI Yueming

doi:10.11999/JEIT250720

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ZHANG Yangyi, GUAN Xinrong, YANG Weiwei, CAO Kuo, WANG Meng, CAI Yueming. IRS Deployment for Highly Time Sensitive Short Packet Communications: Distributed or Centralized Deployment?[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250720

Citation:

ZHANG Yangyi, GUAN Xinrong, YANG Weiwei, CAO Kuo, WANG Meng, CAI Yueming. IRS Deployment for Highly Time Sensitive Short Packet Communications: Distributed or Centralized Deployment?[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250720

Citation:

ZHANG Yangyi, GUAN Xinrong, YANG Weiwei, CAO Kuo, WANG Meng, CAI Yueming. IRS Deployment for Highly Time Sensitive Short Packet Communications: Distributed or Centralized Deployment?[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250720

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IRS Deployment for Highly Time Sensitive Short Packet Communications: Distributed or Centralized Deployment?

doi: 10.11999/JEIT250720 cstr: 32379.14.JEIT250720

1.
National University of Defense Technology, Nanjing 210007, China
2.
Army Engineering University of PLA, Nanjing 210007, China
3.
National University of Defense Technology, Changsha 410073, China

Funds: The National Natural Science Foundation of China (62171461, 62201584, 62171464)

Received Date: 2025-07-31
Accepted Date: 2025-11-05
Rev Recd Date: 2025-11-05

Available Online: 2025-11-13

Abstract

Abstract

Objective The rapid advancement of the Industrial Internet of Things (IIoT) creates latency-sensitive applications such as environmental monitoring and precision control, which depend on short-packet communications and require strict timeliness of information delivery. An Intelligent Reflecting Surface (IRS) is regarded as a feasible method to enhance the reliability and timeliness of these communications because its reflection coefficients can be dynamically adjusted. Previous work has mainly focused on optimizing the phase shifts of IRS elements, whereas the potential gains associated with flexible IRS deployment have not been fully examined. Adjusting the physical placement of IRS units provides additional degrees of freedom that can improve timeliness performance. Two representative deployment strategies, distributed IRS and centralized IRS, form different effective channels and result in different capacity characteristics. This study investigates and compares these deployment modes in IRS-assisted short-packet communication systems. By assessing their Age of Information (AoI) performance under practical channel estimation overheads, the analysis offers guidance on selecting deployment strategies that achieve superior timeliness under diverse system conditions. Methods The paper investigates an IRS-assisted short-packet communication system in which multiple terminal devices transmit short packets to an Access Point (AP) through IRS reflection. Two deployment strategies are considered: distributed and centralized IRS. In the distributed scheme, each device is supported by a dedicated IRS with M reflecting elements positioned nearby. In the centralized scheme, all IRS elements are placed near the AP. The average AoI is used as the performance metric to compare the timeliness of these strategies. The complex distribution of the composite channel gain makes closed-form average AoI analysis difficult. To address this issue, the Moment Matching (MM) approximation is employed to estimate the distribution of the composite channel gain. By incorporating pilot overhead into the analytical model, closed-form expressions for the average AoI of both deployment schemes are obtained, enabling a thorough performance comparison. Results and Discussions Simulation results show that the AoI performance of distributed and centralized IRS deployments differs under varying system conditions. When the IRS carries a large number of reflecting elements, the distributed configuration yields better AoI performance (Fig. 4). Under high transmission power, the centralized configuration presents improved AoI performance (Fig. 5). For scenarios with long AP–device distances, the distributed deployment produces more favorable AoI results (Fig. 6). As the system bandwidth increases, the centralized architecture shows a rapid decrease in AoI and eventually performs better than the distributed configuration (Fig. 7). Conclusions This study provides a comparative analysis of timeliness performance in IRS-assisted short-packet communication systems under distributed and centralized deployment strategies. The MM method is employed to approximate the composite channel gain with a gamma distribution, which supports the derivation of an approximate expression for the average packet error rate. A closed-form expression for the average AoI is then developed by accounting for channel estimation overhead. Simulation results show that the two deployment strategies exhibit different AoI advantages under varying operating conditions. The distributed configuration achieves better AoI performance when a large number of reflecting elements is used or when the AP–device distance is long. The centralized configuration provides improved AoI performance under high transmission power or wide system bandwidth.
- Intelligent Reflecting Surface (IRS),
- Short packet communication,
- Age of Information (AoI)

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References(24)

References

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