Joint Synchronization in Macro-Diversity Multi-Connectivity Networks

2019 
Multi-connectivity is a key enabler for realtime applications demanding high reliability such as connected vehicles. Employing macro-diversity with distributed transceivers has the advantage of mitigating large-scale losses such as shadowing, but may incur time offsets between packets, requiring the receiver to synchronize to each packet individually. Since packet detection is prerequisite for any downstream receiver processing, synchronization can become a bottleneck to achieving high reliability. In this paper, we propose a concept to improve receiver performance in macro-diversity multi-connectivity networks in case of time offsets between packets, for instance, due to loose synchronization of distributed transmitters. By buffering the inputs of parallel receiver paths and allowing for iterative synchronization, successfully detected packets can serve as extended correlation sequence to detect previously undetected packets which thereby become available to diversity combining. Taking link-level simulations of IEEE 802.11 (WLAN) as an example, we demonstrate the efficacy of such Joint Synchronization (JS) and provide first numerical results. We see an SNR gain of about 1 dB in the mid-SNR range, which is equivalent to a packet error rate reduction by an order of magnitude for four-fold diversity. With power consumption in mind, we consider the trade-off between implementation complexity and the gain of JS. We conclude that JS is a viable backwards-compatible approach to improve diversity combining of delayed packets in multi-connectivity networks.
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