# Resource-Efficient Multicast URLLC Service in 5G Systems
## 3 Analyses of Possible Solutions and Their Adaptation to mURLLC  
In this section, we consider solutions aimed to address the problems identified in Section 2. As detailed in Section 1, due to the lack of algorithms/solutions specifically  
\begin{table}
\begin{tabular}{p{56.9 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline
**Time Scale** & **Problem** & **Possible Solutions** & **Recommendations** \\ \hline \multirow{8}{*}{Long-term parameters} & The maximum number of transmission attempts (TXs) & For mURLLC requirements, typically one or two transmission attempts are possible (see Section 3.1). & If the latency budget allows HARQ retransmissions, they shall be enabled. They reduce resource consumption up to three times compared with a single transmission attempt (see Section 4.4). & Out of the three schemes, the NACK-only feedback provides the lowest overall (DL+UL) resource consumption (see Section 4.6). \\ \cline{2-4}  & Feedback Scheme & Three schemes are described in 3 GPP specifications (see Section 3.2). & Out of the three schemes, the NACK-only feedback provides the lowest overall (DL+UL) resource consumption (see Section 4.6). \\ \cline{2-4}  & & The sounding period can be tuned by the gNB. A higher sounding period improves the quality of the precoder (i.e., increases SINRs at UEs) but increases UL overhead (see Section 3.3). & For low UE speed, sounding period optimization can reduce resource consumption up to 40\%. For high UE speed, a high sounding period only increases UL overhead without a notable reduction of DL resource consumption (see Section 4.7). \\ \hline \multirow{8}{*}{Short-term parameters} & Precoder & Existing algorithms can be classified into (see Section 3.4): & For a low number of antennas, iterative algorithms provide the highest performance with reasonable complexity. For the M-MIMO case, orthogonal subspace construction algorithms provide better results (see Section 4.2). \\ \cline{2-4}  & & & \\ \cline{2-4}  & & & \\ \cline{2-4}  & & & \\ \cline{2-4}  & & & \\ \cline{2-4}  & & & \\ \cline{2-4}  & & & \\ \cline{2-4}  & & & \\ \cline{2-4}  & & & \\ \cline{2-4}  & & & \\ \cline{2-4}  & & & \\ \hline \multirow{8}{*}{Short-term parameters (for each TX)} & RB allocation (scheduler) & The EDF scheduler aims to minimize the latency required for mURLLC [28]. It can be implemented in several ways (see Section 3.5): & FS EDF provides notable gain only for a low number of UEs and a low number of antennas at the gNB. In other cases, Non-FS EDF provides the same performance with up to 40\% lower complexity (see Section 4.3). \\ \cline{2-4}  & MCS selection & MCS selection depends on the feedback scheme (see Section 3.6). & The usage of feedback and multicast OLLA up to three times reduces the overall resource consumption. In the case of two TXs, different target BLERs for the first and second TXs reduce resource consumption up to 40\% compared with the same BLERs (see Section 4.5). \\ \cline{2-4}  & & & \\ \hline \end{tabular}
\end{table}
Table 2: Summary of the considered problems and possible solutions.  
developed for mURLLC, in this paper, we adapt the solutions proposed either for broadband multicast traffic or for unicast URLLC traffic. In the latter case, we show how to extend/modify solutions such that they can work with multiple receivers.  
The following sections are structured as follows. First, we analyze how the gNB can select long-term transmission parameters: the maximum number of transmission attempts, the feedback scheme, and the sounding period. Then, we consider how the gNB selects parameters for each particular transmission: the precoder, RBs, and the MCS.