Sensing-based Grant-Free Scheduling for Ultra Reliable Low Latency and Deterministic Beyond 5G Networks

Author(s):  
M.Carmen Lucas-Estan ◽  
J. Gozalvez
Keyword(s):  
Author(s):  
Soheil Rostami ◽  
Kari Heiska ◽  
Oleksandr Puchko ◽  
Kari Leppanen ◽  
Mikko Valkama

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 192808-192834
Author(s):  
Delia Rico ◽  
Pedro Merino
Keyword(s):  

Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3449 ◽  
Author(s):  
Kelechi ◽  
Alsharif ◽  
Ramly ◽  
Abdullah ◽  
Nordin

Network latency will be a critical performance metric for the Fifth Generation (5G) networks expected to be fully rolled out in 2020 through the IMT-2020 project. The multi-user multiple-input multiple-output (MU-MIMO) technology is a key enabler for the 5G massive connectivity criterion, especially from the massive densification perspective. Naturally, it appears that 5G MU-MIMO will face a daunting task to achieve an end-to-end 1 ms ultra-low latency budget if traditional network set-ups criteria are strictly adhered to. Moreover, 5G latency will have added dimensions of scalability and flexibility compared to prior existing deployed technologies. The scalability dimension caters for meeting rapid demand as new applications evolve. While flexibility complements the scalability dimension by investigating novel non-stacked protocol architecture. The goal of this review paper is to deploy ultra-low latency reduction framework for 5G communications considering flexibility and scalability. The Four (4) C framework consisting of cost, complexity, cross-layer and computing is hereby analyzed and discussed. The Four (4) C framework discusses several emerging new technologies of software defined network (SDN), network function virtualization (NFV) and fog networking. This review paper will contribute significantly towards the future implementation of flexible and high capacity ultra-low latency 5G communications.


Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 490
Author(s):  
Yaqin Song ◽  
Hong Ni ◽  
Xiaoyong Zhu

Fifth generation (5G) networks have a high requirement for low latency of data delivery. Information-centric networking (ICN) adopts the paradigm of separation of the identifier and locator. It is efficient in content distribution by supporting in-network caching and has the potential to satisfy the low latency requirement in 5G. Replica selection is a key problem to retrieving content in ICN. Prior research usually utilizes the nearest replica. However, using the nearest replica cannot guarantee the smallest content download delay. To exploit in-network caching better, we propose an enhanced replica selection approach, called ERS. ERS first uses a distance-constrained-based name resolution system to discover the nearby replicas. Then, the most appropriate replica is chosen according to a local state table that maintains the state of replica nodes within a limited domain. In addition to network distance and replica node load, ERS innovatively introduces the path congestion degree between requester and replica nodes to assist replica selection. With extensive simulations, the proposed approach shows better performance than the state-of-the-art methods in terms of average content download delay. Finally, the overhead of the proposed method is analyzed.


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