Dynamic Framing and Power Allocation for Real-Time Wireless Networks with Variable-Length Coding: A Tandem Queue Approach

Ensuring high reliability and low latency poses challenges for numerous applications that require rigid performance guarantees, such as industrial automation and autonomous vehicles. Our research primarily concentrates on addressing the real-time requirements of ultra-reliable low-latency communication (URLLC). Specifically, we tackle the challenge of hard delay constraints in real-time transmission systems, overcoming this obstacle through a finite blocklength coding scheme. In the physical layer, we encode randomly arriving packets using a variable-length coding scheme and transmit the encoded symbols by truncated channel inversion over parallel channels. In the network layer, we model the encoding and transmission processes as tandem queues. These queues backlog the data bits waiting to be encoded and the encoded symbols to be transmitted, respectively. This way, we represent the system as a two-dimensional Markov chain. By focusing on instances when the symbol queue is empty, we simplify the Markov chain into a one-dimensional Markov chain, with the packet queue being the system state. This approach allows us to analytically express power consumption and formulate a power minimization problem under hard delay constraints. Finally, we propose a heuristic algorithm to solve the problem and provide an extensive evaluation of the trade-offs between the hard delay constraint and power consumption.