@article{lee_choi_dai_2016, title={Joint User Selection and Feedback Bit Allocation Based on Sparsity Constraint in MIMO Virtual Cellular Networks}, volume={15}, ISSN={["1558-2248"]}, DOI={10.1109/twc.2015.2497702}, abstractNote={In this paper, we jointly consider the user selection and feedback design problems in a virtual cellular network (VCN), where multiple base stations (BSs) share a user set. In many practical systems, the uplink feedback channel is generally shared by multiple users. Thus, the feedback budget allocated to unselected users not only wastes the feedback resources, but harms the system throughput by decreasing the available feedback budget for the selected users. We optimize both the user selection and feedback bit allocation based on long-term average channel information of the users. We first analyze the effects of the quantization error on the average achievable rate of the VCN system. Next, we propose a user selection and feedback bit allocation protocol under each BS's sum feedback rate constraint as well as the sparsity constraint on all users' feedback sizes. We show that the joint optimization problem can be decoupled into several NP-hard subproblems, one for each BS. We describe the brute-force searching algorithm for the optimal solution, and propose an efficient algorithm with significantly reduced computational complexity by relaxing the sparsity constraint on the feedback sizes. As a result, only the selected users exploit the uplink feedback budget, and the system performance is improved.}, number={3}, journal={IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS}, author={Lee, Jung Hoon and Choi, Wan and Dai, Huaiyu}, year={2016}, month={Mar}, pages={2069–2079} }
 @article{lee_dai_2015, title={Nash Bargaining in Beamforming Games with Quantized CSI in Two-user Interference Channels}, ISSN={["2334-0983"]}, DOI={10.1109/glocom.2015.7417263}, abstractNote={In this paper, we consider a beamforming game of the transmitters in a two-user multiple-input single- output interference channel using limited feedback and investigate how each transmitter should find a strategy from the quantized channel state information (CSI). In the beamforming game, each transmitter (a player) tries to maximize the achievable rate (a payoff function) via a proper beamforming strategy. In our case, each transmitter's beamforming strategy is represented by a linear combining factor between the maximum-ratio transmission (MRT) and the zero-forcing (ZF) beamforming vectors, which is shown to be a Pareto optimal achieving strategy. With the perfect CSI, each transmitter can know the exact achievable rate region, and hence can find the beamforming strategy corresponding to any point in the achievable rate region. With limited feedback, however, the transmitters can only conjecture the achievable rate region from the quantized CSI, so their optimal strategies may not be optimal anymore. Considering the quantized CSI at the transmitter, we first find the Nash equilibrium in a non-cooperative game. Then, in a cooperative (Nash bargaining) game, we find a Nash bargaining solution and test its validity. Finally, we propose three bargaining solutions that improve the validity of the cooperation or the average Nash product. Our proposed bargaining solutions utilize the codebook structure; instead of each quantized channel itself, its Voronoi region is considered.}, journal={2015 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM)}, author={Lee, Jung Hoon and Dai, Huaiyu}, year={2015} }
 @article{lee_choi_2015, title={Unified codebook design for vector channel quantization in MIMO broadcast channels}, volume={63}, number={10}, journal={IEEE Transactions on Signal Processing}, author={Lee, J. H. and Choi, W.}, year={2015}, pages={2509–2519} }