HARQ-based Quantized Average Consensus over Unreliable Directed Network Topologies
In this paper, we propose a distributed algorithm (herein called HARQ-QAC) that enables nodes to calculate the average of their initial states by exchanging quantized messages over a directed communication network. In our setting, we assume that our communication network consists of unreliable communication links (i.e., links suffering from packet drops). For countering link unreliability our algorithm leverages narrowband error-free feedback channels for acknowledging whether a packet transmission between nodes was successful. Additionally, we show that the feedback channels play a crucial role in enabling our algorithm to exhibit finite-time convergence. We analyze our algorithm and demonstrate its operation via an example, where we illustrate its operational advantages. Finally, simulations corroborate that our proposed algorithm converges to the average of the initial quantized values in a finite number of steps, despite the packet losses. This is the first quantized consensus algorithm in the literature that can handle packet losses and converge to the average. Additionally, the use of the retransmission mechanism allows for accelerating the convergence.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
SharQ: Bridging Activation Sparsity and FP4 Quantization for LLM Inference
Low-bit floating-point formats and semi-structured sparsity are increasingly supported by modern accelerators, yet combining them for LLM activation compression remains challenging: activations contain input-dependent ou…
Video GenerationDistributed Average Consensus under Quantized Communication via Event-Triggered Mass Splitting
We study the distributed average consensus problem in multi-agent systems with directed communication links that are subject to quantized information flow. The goal of distributed average consensus is for the nodes, each…
QuantizationEvent-Triggered Quantized Average Consensus via Mass Summation
We study the distributed average consensus problem in multi-agent systems with directed communication links that are subject to quantized information flow. The goal of distributed average consensus is for the nodes, each…
QuantizationDistributed Average Consensus under Quantized Communication via Event-Triggered Mass Summation
We study distributed average consensus problems in multi-agent systems with directed communication links that are subject to quantized information flow. The goal of distributed average consensus is for the nodes, each as…
QuantizationARQ-based Average Consensus over Directed Network Topologies with Unreliable Communication Links
In this paper, we address the discrete-time average consensus problem in strongly connected directed graphs, where nodes exchange information over unreliable error-prone communication links. We enhance the Robustified Ra…