김준헌 교수

On-demand video streaming is becoming a killer application for wireless networks. Recent information-theoretic results have shown that a combination of caching on the users' devices and device-to-device (D2D) communications yields throughput scalability for very dense networks, which represent critical bottlenecks for conventional cellular and wireless local area network (WLAN) technologies. In this paper, we consider the implementation of such caching D2D systems where each device pre-caches a

This paper proposes fast millimeter-wave (mm-wave) beam training protocols with receive beamforming. Both IEEE standards and the academic literature have generally considered beam training protocols involving exhaustive search over all possible beam directions for both the beamforming initiator and responded However, this operation requires a long time (and thus overhead) when the beamwidth is quite narrow such as for mm-wave beams (1° in the worst case). To alleviate this problem, we propose tw

Millimeter-wave (mm-wave) transmission is a promising method for increasing capacity in next-generation cellular systems. However, since mm-wave signals are too weak to (i) do long-distance communication and (ii) survive in non-line-of-sight situations, multi-hop relaying is required. We thus study in this paper a multi-hop routing protocol at mm-wave (38 GHz and 28GHz) frequencies. Due to the great and steadily increasing importance of video streaming in cellular applications, we pay special at

This paper addresses an adaptive and dynamic localized scheme unique to hierarchical clustering protocols in wireless sensor networks, while reducing the consumption of residual energy of cluster heads and as a result delivering a prolonged sensor network lifetime. Our proposed scheme, low-energy localized clustering (LLC) aims to minimize energy consumption of cluster heads while the entire sensor network is still being covered. For achieving this goal, LLC dynamically regulates the radius of e

This paper proposes two novel algorithms for adaptive crowdsourcing in 60-GHz medical imaging big-data platforms, namely, a max-weight scheduling algorithm for medical cloud platforms and a stochastic decision-making algorithm for distributed power-and-latency-aware dynamic buffer management in medical devices. In the first algorithm, medical cloud platforms perform a joint queue-backlog and rate-aware scheduling decisions for matching deployed access points (APs) and medical users where APs are

With the evolution of various advanced driver assistance system (ADAS) platforms, the design of autonomous driving system is becoming more complex and safety-critical. The autonomous driving system simultaneously activates multiple ADAS functions; and thus it is essential to coordinate various ADAS functions. This paper proposes a randomized adversarial imitation learning (RAIL) method that imitates the coordination of autonomous vehicle equipped with advanced sensors. The RAIL policies are trai

Wireless systems operating in the 60 GHz band are promising for achieving broadband connectivity to/from high-speed trains. However, the high mobility creates new challenges on the physical and medium access control (MAC) layer and requires a dedicated infrastructure of closely-spaced base stations near the train tracks. We develop an optimization framework for selecting the pairs between infrastructure stations and the antennas on the train to achieve sum rate maximization. We investigate the m