Resource Allocation For Reconfigurable Intelligent Surface Assisted Dual Connectivity

<p>The next generation 6G wireless systems are envisioned to have higher reliability and capacity than the existing cellular systems. The reconfigurable intelligent surfaces (RISs) is one of the promising solution to control the wireless channel by altering the electromagnetic properties of the signal. The dual connectivity (DC) increases the per-user throughput by utilizing radio resources from two different base stations. In this work, we propose the RIS assisted DC system to improve the per-user throughput of the users by utilizing resources from two base stations (BSs) in proximity via different RISs. Given an fairness based utility function, the joint resource allocation and the user scheduling of RIS assisted DC system is formulated as an optimization problem and the optimal user scheduling time fraction is derived. The heuristic is proposed to solve the formulated optimization problem with the derived optimal scheduling time fractions. The exhaustive simulation results for coverage and throughput of the RIS assisted DC system are presented with varying user, BS, blockage, and RIS densities for different fairness values. Further, we show that the proposed RIS assisted DC system provides significant throughput gain of 52% and 48% in certain scenarios when compared to the existing benchmark and DC systems.</p>

Resource Allocation For Reconfigurable Intelligent Surface Assisted Dual Connectivity

<p>The next generation 6G wireless systems are envisioned to have higher reliability and capacity than the existing cellular systems. The reconfigurable intelligent surfaces (RISs) is one of the promising solution to control the wireless channel by altering the electromagnetic properties of the signal. The dual connectivity (DC) increases the per-user throughput by utilizing radio resources from two different base stations. In this work, we propose the RIS assisted DC system to improve the per-user throughput of the users by utilizing resources from two base stations (BSs) in proximity via different RISs. Given an fairness based utility function, the joint resource allocation and the user scheduling of RIS assisted DC system is formulated as an optimization problem and the optimal user scheduling time fraction is derived. The heuristic is proposed to solve the formulated optimization problem with the derived optimal scheduling time fractions. The exhaustive simulation results for coverage and throughput of the RIS assisted DC system are presented with varying user, BS, blockage, and RIS densities for different fairness values. Further, we show that the proposed RIS assisted DC system provides significant throughput gain of 52% and 48% in certain scenarios when compared to the existing benchmark and DC systems.</p>

RB Allocation Scheme for eMBB and URLLC Coexistence in 5G and Beyond

In this paper, we studied resource allocation in a dynamic multiplexing scenario of two 5G services, namely, enhanced mobile broadband (eMBB) and ultrareliable low-latency communication (URLLC). Considering that eMBB services focus on high data rates while URLLC is very strict in terms of latency and reliability, we formulate a joint eMBB/URLLC resource allocation problem. To solve the formulated problem, in particular, we propose a joint resource allocation algorithm that can satisfy both eMBB user rate and URLLC interrupt probability requirements. We propose an RB allocation scheme that takes into account the needs of eMBB and URLLC users. The program consists of two phases as follows: (1) establish an RB allocation for eMBB users and (2) assign the minislot for URLLC users and calculate the transmission power of URLLC users that ensures the reliability constraint. We also realize and verify the algorithm through the simulation.