COMPARISON OF DOWNLINK SCHEDULING AND RESOURCE ALLOCATION FOR 5G MIMO-MULTICARRIER SYSTEMS

Multiple-Input Multiple-Output (MIMO) is a well-established technology in wireless communication systems and a key feature of several 3G and 4G cellular standards. With the latest 5G, the preferred PHY layer modulation format had been indecisive, and several options like orthogonal frequency division multiplexing (OFDM), a traditional approach and filter-bank multicarrier / offset quadrature amplitude modulation (FBMC/OQAM) with improved spectral efficiency have been proposed. In these systems, scheduling and resource allocation (SRA) algorithms become important in enhancing resource utilization by assigning transmission data rates, bandwidth, and power, while at the same time handling multimedia applications with different quality-of-service (QoS) requirements. This paper strives to present an expansive comparison of both the modulation formats by proposing two cross-layer SRA framework (Greedy and Dynamic) in practical scenarios of 5G deployment through performance-related metrics such as goodput, delay, and fairness. The achieved experimental results demonstrate the overall superior performance of dynamic FBMC/OQAM compared to greedy based SRA. On the fairness aspect, however, OFDM performs better with about 10% more average fairness index than FBMC/OQAM.Cyclostationary feature and Matched Filter detection for a primary user on a GSM900 signal over a Rayleigh Fading channel. In addition, the project will also simulate and analyze the performance of the co-operative sensing technique using different numbers of secondary users, and review how it seeks to solve the hidden node problem.

Design Specifications

  • OFDM and FBMC

  • ETU and EPA Channel Model

  • OFDM-SVD and ZF

  • OFDM using 4QAM,16 QAM,32 QAM,64 QAM Modulation Methods

  • FBMC using OQAM-SVD and ZF

Reference Paper: Downlink Scheduling and Resource Allocation for 5G MIMO-Multicarrier: OFDM vs FBMC/OQAM

Author’s Name: Guillem Femenias,Felip Riera-Palou,Xavier Mestre,and Joan J. Olmos

Source: IEEE

Year:2017

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