文件列表:

IEEE JSAC.pdf (218240, 2020-04-30)
V1.1 (0, 2020-04-29)
V1.1\A_precoder.m (2388, 2020-04-29)
V1.1\CVX_PA.m (1573, 2020-04-29)
V1.1\CVX_PA0.m (668, 2020-04-29)
V1.1\D_precoder.m (389, 2019-10-09)
V1.1\E_power0.m (476, 2019-10-15)
V1.1\N_power0.m (573, 2019-10-15)
V1.1\PA.m (1324, 2020-04-29)
V1.1\PA0.m (263, 2020-04-29)
V1.1\Precoder.m (1505, 2018-01-03)
V1.1\array_respones.m (158, 2017-12-06)
V1.1\data.xlsx (9021, 2019-11-04)
V1.1\generate_channel.m (714, 2019-11-20)
V1.1\main_SR.m (3591, 2020-04-30)
V1.1\myfun.m (1593, 2020-04-29)
V1.1\myfun0.m (202, 2020-04-29)
V1.1\user_grouping.m (592, 2017-12-27)

This simulation code package is mainly used to reproduce the results of the following paper [1]: [1] Linglong Dai, Bichai Wang, Mugen Peng, and Shanzhi Chen, °Hybrid Precoding-Based Millimeter-Wave Massive MIMO-NOMA with Simultaneous Wireless Information and Power Transfer,±to appear in IEEE Journal on Selected Areas in Communications, 2018. ********************************************************************************************************************************* If you use this simulation code package in any way, please cite the original paper [1] above. The author in charge of this simulation code pacakge is: Bichai Wang (email: wbc15@mails.tsinghua.edu.cn). Reference: We highly respect reproducible research, so we try to provide the simulation codes for our published papers (more information can be found at: http://oa.ee.tsinghua.edu.cn/dailinglong/publications/publications.html). Please note that the MATLAB R2010b is used for this simulation code package, and there may be some imcompatibility problems among different MATLAB versions. Copyright reserved by the Broadband Communications and Signal Processing Laboratory (led by Dr. Linglong Dai), Tsinghua National Laboratory for Information Science and Technology (TNList), Department of Electronic Engineering, Tsinghua University, Beijing 100084, ***. ********************************************************************************************************************************* Abstract of the paper: Non-orthogonal multiple access (NOMA) has been recently considered in millimeter-wave (mmWave) massive MIMO systems to further enhance the spectrum efficiency. In addition, simultaneous wireless information and power transfer (SWIPT) is a promising solution to maximize the energy efficiency. In this paper, for the first time, we investigate the integration of SWIPT in mmWave massive MIMO-NOMA systems. As mmWave massive MIMO will likely use hybrid precoding (HP) to significantly reduce the number of required radio-frequency (RF) chains without an obvious performance loss, where the fully digital precoder is decomposed into a high-dimensional analog precoder and a low-dimensional digital precoder, we propose to apply SWIPT in HP-based MIMO-NOMA systems, where each user can extract both information and energy from the received RF signals by using a power splitting receiver. Specifically, the cluster-head selection (CHS) algorithm is proposed to select one user for each beam at first, and then the analog precoding is designed according to the selected cluster heads for all beams. After that, user grouping is performed based on the correlation of users' equivalent channels. Then, the digital precoding is designed by selecting users with the strongest equivalent channel gain in each beam. Finally, the achievable sum rate is maximized by jointly optimizing power allocation for mmWave massive MIMO-NOMA and power splitting factors for SWIPT, and an iterative optimization algorithm is developed to solve the non-convex problem. Simulation results show that the proposed HP-based MIMO-NOMA with SWIPT can achieve higher spectrum and energy efficiency compared with HP-based MIMO-OMA with SWIPT. ********************************************************************************************************************************* How to use this simulation code package? All figures can be derived by running the corresponding m file (main_SR.m). The package contains 17 additional Matlab functions. These functions are called by the Matlab scripts. ********************************************************************************************************************************* Enjoy the reproducible research!

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