Joint Power and Resource Block Allocation for Mixed-Numerology-Based 5G Downlink Under Imperfect CSI

• Published in: IEEE open journal of the Communications Society Vol. 1; pp. 1583 - 1601
• Main Authors: Korrai, Praveen Kumar, Lagunas, Eva, Bandi, Ashok, Sharma, Shree Krishna, Chatzinotas, Symeon
• Format: Journal Article
• Language: English
• Published: New York IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G mobile communication; Broadband; Downlinking; eMBB; Frame structures; mixednumerologies; Mobile computing; Network latency; Optimization; power minimization; Quality of service; Quality of service architectures; Radio access networks; RAN resource slicing; Reliability; resource block allocation; Resource management; Resource scheduling; Slicing; Ultra reliable low latency communication; URLLC and mMTC; Wireless networks
• ISSN: 2644-125X; 2644-125X
• DOI: 10.1109/OJCOMS.2020.3029553

Fifth-generation (5G) of wireless networks are expected to accommodate different services with contrasting quality of service (QoS) requirements within a common physical infrastructure in an efficient way. In this article, we address the radio access network (RAN) slicing problem and focus on the three 5G primary services, namely, enhanced mobile broadband (eMBB), ultra-reliable and low-latency communications (URLLC) and massive machine-type communications (mMTC). In particular, we formulate the joint allocation of power and resource blocks to the heterogeneous users in the downlink targeting the transmit power minimization and by considering mixed numerology-based frame structures. Most importantly, the proposed scheme does not only consider the heterogeneous QoS requirements of each service, but also the queue status of each user during the scheduling of resource blocks. In addition, imperfect Channel State Information (CSI) is considered by including an outage probabilistic constraint into the formulation. The resulting non-convex problem is converted to a more tractable problem by exploiting Big-M formulation, probabilistic to non-probabilistic transformation, binary relaxation and successive convex approximation (SCA). The proposed solution is evaluated for different mixed-numerology resource grids within the context of strict slice-isolation and slice-aware radio resource management schemes via extensive numerical simulations.