## 2 System Model
### The Queueing Model in the Network Layer  
As shown in Figure 2, we characterize the packet transmission dynamics in the network layer using a packet queuing model. Queuing effects arise due to the fact that the coding's blocklength may require multiple time slots for transmission. Consequently, the transmission process is conceptualized as the symbol queue. The packet queue and symbol queue together form a tandem queue.  
To begin with, let us introduce the packet queue. Suppose that data packets of size \(A\) bits arrive deterministically at the transmitter in each time slot. We define queue length, \(q_{1}[t]\), in terms of the number of packets waiting in the queue. In particular, \(q_{1}[t]\) evolves as \[q_{1}[t+1]=\min\Bigl{\{}(q_{1}[t]-s_{1}[t])^{+}+1,K\Bigr{\}}, \tag{7}\]  
where \((x)^{+}=\max\{x,0\}\), and \(K\) is the maximum queue length constrained by the buffer size. Moreover, \(s_{1}[t]\) denotes the service rate in terms of the number of data packets transmitted in time slot \(t\).  
Considering Equation (5), the achievable channel coding rate in finite blocklength coding increases with the coding blocklength. Consequently, it is more power-efficient to accumulate a sufficient number of packets before the coding process. We propose a greedy framing policy, where all packets in the packet queue undergo finite blocklength coding when the symbol queue is empty. Consequently, the service rate of the packet queue is given by  
\[s_{1}[t]=\left\{\begin{array}{cl}q_{1}[t]&\text{if }q_{2}[t]=0,\\ 0&\text{if }q_{2}[t]>0,\end{array}\right. \tag{8}\]  
Subsequently, a detailed introduction to the symbol queue is provided. Throughout the finite blocklength coding process, the data packets transmitted by the packet queue \(s_{1}[t]\), each encompassing \(A\) bits, are encoded into \(m[t]\) symbols. The relationship between the service rate of the packet queue \(s_{1}[t]\) and the coding blocklength \(m[t]\) is given by  
\[m[t]=\frac{As_{1}[t]}{r[t]}. \tag{9}\]  
The encoded symbols are buffered in a symbol queue and transmitted over a time-varying fading channel across multiple time slots. The symbol queue's length \(q_{2}[t]\) is defined as the number of symbol blocks backlogged in the symbol queue in the \(t\)-th time slot. Each symbol block spans \(T\) s and \(B\) Hz in the time and spectral domains, respectively. Subsequently, the arrival rate of the symbol queue \(a_{2}[t]\) is defined as the number of symbol blocks that arrive. The service rate of the symbol queue \(s_{2}[t]\) is defined as the number of symbol blocks transmitted in the \(t\)-th time slot. Consequently, the evolution of the symbol queue \(q_{2}[t]\) is defined as  
\[q_{2}[t+1]=\left\{\begin{array}{cl}(a_{2}[t]-s_{2}[t])^{+}&\text{if }q_{2}[t]=0,\\ q_{2}[t]-s_{2}[t]&\text{if }q_{2}[t]>0,\end{array}\right. \tag{10}\]  
During the encoding process, the data packets can be encoded into multiple symbols. The number of symbols that can be transmitted in each time slot is generally multiple and contingent upon the available channel resources. When the system is allocated \(T\) s and \(B\) Hz as its channel resources, we set \(s_{2}[t]=1\). Subsequently, the coding blocklength \(m[t]\) can be quantified as the number of symbol blocks \(a_{2}[t]\). Then, \(a_{2}[t]\) is formulated as  
\[a_{2}[t]=\left\lceil\frac{m[t]}{2 BT}\right\rceil=\left\lceil\frac{As_{1}[t]}{2 BTr[t]}\right\rceil. \tag{11}\]  
The ceiling function has been utilized in Equation (11) to account for the symbol blocks being discrete units. The use of variable-length coding introduces variability in the transmission time. The constructed symbol queue is designed to indicate the transmission process of symbols. Consequently, communication signalling based on the symbol queue can prompt the receiver to commence decoding.