Access parameters, user equipment (UE) density, system load, and channel conditions significantly impact the performance of random-access (RA) protocols, influencing network capacity, latency, and robustness. In 3GPP standard, the prach-ConfigurationIndex access parameter is used to designate reserved RA channel occasions (ROs) for each beam, enabling UEs to derive beam mapping patterns and select desired beams through a beam-based RA protocol. This article addresses the challenge of bursty arrivals from massive Internet of Things (IoT) devices with sporadic traffic patterns in 5G beamforming networks. We propose an analytical model to evaluate the performance of the beam-based RA protocol for any beam mapping pattern. Extensive computer simulations are conducted to validate the accuracy and effectiveness of our model across various scenarios. The results demonstrate that our model provides valuable insights into the behavior and performance of the beam-based RA protocol and offers a reliable tool to evaluate and optimize beam mapping patterns in practical 5G network deployments.

We design, implement, and evaluate an H.264/SVC decoder and an HTTP video streaming client on multi-core mobile devices. The decoder employs multiple decoder threads to leverage the multi-core CPUs, and the streaming server/client support adaptive HTTP video streaming. To evaluate the decoder performance, we conduct experiments using real H.264/SVC videos on a tablet and a smart phone running Android 4.0. Our experimental results demonstrate that real-time H.264/SVC decoding is feasible on multi-core mobile devices. For example, for 960×544 videos, our decoder achieves up to 20.72 FPS (Frame-Per-Second), and for 480×272 videos, it achieves up to 42.03 FPS. We also conduct extensive HTTP video streaming experiments over live WiFi and 3G cellular networks, which show that high frame rate (up to ~42 FPS), and short initial delay (as small as ~2.5 sec) are possible. We make our testbed publicly available to the research communities.

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We propose region- and action-aware virtual world clients. To develop such clients, we present a parameterized network traffic model, based on a large collection of Second Life traces gathered by us. Our methodology is also applicable to virtual worlds other than Second Life. With the traffic model, various optimization criteria can be adopted, including visual quality, response time, and energy consumption. We use energy consumption as the show case, and demonstrate via trace-driven simulations that, compared to two existing schemes, a mobile client can save up to 36% and 41% communication energy by selectively turning on its WiFi network interface.

Today's mobile Internet is heavily overloaded by the increasing demand and capability of mobile devices, in particular, multimedia traffic. However, not all traffic is created equal, and a large portion of multimedia contents on the mobile Internet is delay tolerant. We study the problem of capitalizing the content transfer opportunities under better network conditions via postponing the transfers without violating the user-specified deadlines. We propose a new framework called SmartTransfer, which offers a unified content transfer interface to mobile applications. We also develop two scheduling algorithms to opportunistically schedule the content transfers. Via extensive trace-driven simulations, we show that our algorithms outperform a baseline scheduling algorithm by far: up to 17 times improvement in upload throughput and/or at most 20 dBm boost in signal strength. The simulation results also reveal various tradeoff between the two proposed scheduling algorithms. We have implemented our framework and one of the scheduling algorithms on Android, to demonstrate their practicality and efficiency.

A design of MPEG-2 and H.264/AVC video decoder is demonstrated in a 0.18?m CMOS [1]. The key design issues involved in this advanced IC are discussed, including improving area and power efficiency. Power dissipation is greatly lowered through the architectural exploration. Measurement results show that MPEG-2 and H.264/AVC real-time decoding of [email protected] are achieved at 1.15MHz with power dissipation of 108?W and 125?W respectively at 1V supply voltage.