Multi-Tier Caching for Statistical-QoS Driven Digital Twins Over mURLLC-Based 6G Massive-MIMO Mobile Wireless Networks Using FBC

Abstract

Digital Twin (DT) has been widely envisioned as a major intelligent application of 6G wireless networks requiring stringent quality-of-service (QoS) for massive ultra-reliable and low latency communications (mURLLC) to support efficient interactions between physical and virtual objects. As a key multi-tier computing (MTC) technique of 6G mobile networks, multi-tier caching stores the highly-demanded data at different wireless network tiers to significantly reduce mURLLC-streaming delay and data move. However, how to efficiently cache mURLLC data at different caching tiers in wireless networks and how to support both delay and error-rate bounded QoS for DT remain challenging problems. To conquer these difficulties, in this paper we propose to integrate multi-tier caching with finite blocklength coding for supporting mURLLC-based DT by developing multi-tier 6G massive-multiple-input-multiple-output (M-MIMO) mobile networks. First, we develop the efficient inter-tier and intra-tier collaborative multi-tier caching mechanisms, where popular DT data items are selectively cached at different wireless network caching tiers including: router tier, M-MIMO base-station (BS)/WiFi-AP tier, and mobile device tier. Second, our proposed inter-tier caching mechanisms maximize the aggregate caching gain , in terms of DT-based $\epsilon$-effective capacity , across three caching tiers to support statistical delay and error-rate bounded QoS. Third, we develop the intra-tier caching algorithm to optimize each caching-tier's QoS. Finally, our extensive numerical analyses show our developed schemes' performances-superiorities over existing schemes.