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W e investigate packet discarding schemes f o r TCP over ATM with U B R service. In doing so, we tested the eflective throughput of two existing schemes, Partial Pnwlcet Discard(PPD) and Early Packet Discard(EPD), as compared to the Random Cell Discard(RCD) scheme which discards any incoming cells after buger overflow. W e observed that P P D alleviates the effect of packet fragmentation so that it gets effective throughput enhancement over RCD, and E P D provides further enhancement over PPD. After closer investigation, we found that there is a sustained congestion problem other than packet fragmentation that causes the effective throughput to be degraded. W e noted that sustained congestion resulted in the synchronization of TCP window expansion and shrinkage. To provide a solution for this problem, we propose the Early Selective Packet Discard(ESPD) policy, a strategy which makes sessions take turns in accessing network capacity by discarding packets from selected sessions rather than randomly. Our results shows that ESPD achieves throughput and fairness enhancement over EPD with only a modest increase in implementation complexity.

This paper proposes a neural 5G traffic generation model and a methodology for calculating spectrum requirements of private 5G networks to provide various industrial communication services. To accurately calculate the spectral requirements, it is necessary to analyze the actual data volume and traffic type of industrial cases. However, since there is currently no suitable traffic model to test loads in private 5G networks, we have developed a generative adversarial network (GAN)-based traffic generator that can generate realistic traffic by learning actual traffic traces collected by mobile network operators. In addition, in the case of industrial applications, probability-based traffic models were also used in parallel because there were not enough real data to be learned. The proposed 5G traffic generation model is combined with the proposed 5G spectrum calculation methodology, enabling more accurate spectrum requirements calculation through traffic simulation similar to the real-life environment. In this paper, spectrum requirements are calculated differently according to the two duplexing types of frequency division duplexing (FDD) and time division duplexing (TDD). As a guide for companies that will provide advanced wireless connectivity for a wide variety of vertical industries using 5G networks, we simulated eight use cases defined in the 5G Alliance for Connected Industries and Automation (ACIA) white paper. Spectrum requirements were calculated under the various simulation conditions considering varying traffic loads, deployment scenarios, and duplexing schemes. Various simulation results have confirmed that a bandwidth of at least 22.0 MHz to a maximum of 397.8 MHz is required depending on the deployment scenario.