Optimization of Physical Uplink Resource Allocation in 5G Cellular Network using Monte Carlo Tree Search

University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

Abstract: The Physical Uplink Control Channel (PUCCH), which is mainly used to transmit Uplink Control Information (UCI), is a key component to enable the 5G NR system. Compared to LTE, NR specifies a more flexible PUCCH structure to support various applications and use cases. In the literature, however, an optimized solution that exploits those degrees of freedom is missing and fixed-heuristic solutions are just implemented in current 5G networks. Consequently, the predefined PUCCH format configuration is inefficient because it proposes a one-size-fits-all solution. In short, the number of symbols dedicated to PUCCH resources are often pre-determined and fixed without considering the UE’s specific needs and requirements. Failure to exploit the diversity of PUCCH format configurations and sticking to the one-size-fits-all solution, translates into a poor PUCCH resource allocation in the physical grid. To overcome this, a solution is presented by introducing a more efficient PUCCH re-distribution algorithm that exploits the same Physical Resource Block (PRB) domain. This leads into a combinatorial optimization problem with the objective of minimizing the PRBs utilization while maximizing the number of resources allocated and, in essence, the number of UEs “served”. For this purpose, we utilize a Monte Carlo Tree Search (MCTS) method to find the optimal puzzle on the grid, which offers clear advantages in search time benchmarked against an exhaustive search method. A wide variety of cases and scenario-dependent solutions are allowed using this puzzling technique. Overall results indicate that the optimal solutions devised by MCTS in conjunction with the new resource allocation algorithm bring substantial improvement compared to the one-size-fits-all baseline. In particular, this novel implementation, nonexistent to date in the 3GPP standard, reduces the dedicated PUCCH resource region by 1=6 without sacrificing any user’s allocation, while reusing the remaining PRBs (an increase of up to 11:36%) for the UL data channel or PUSCH. As a future work, we expect to observe similar improvements in higher layers metrics and KPIs, once link-level reception details are implemented and simulated for UL control channels based on our resource allocation solution. 

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