首页> 外文会议>IEEE Wireless Communications and Networking Conference >User Association in Massive MIMO and mmWave Enabled HetNets Powered by Renewable Energy
【24h】

User Association in Massive MIMO and mmWave Enabled HetNets Powered by Renewable Energy

机译:MASHIVE MIMO和MMWAVE中的用户关联启用了可再生能源的Hetnets

获取原文

摘要

This paper considers a hybrid heterogeneous network (HetNet), where macro cells adopt massive multiple-input multiple-output (MIMO), and small cells adopt millimeter wave (mmWave) transmissions. We assume that all base stations (BSs) are solely powered by the renewable energy. The implementation of these emerging techniques has a substantial effect on the user association (UA). Motivated by this, we formulate a user association problem to maximize the network utility while the power cost of each BS does not exceed the harvested energy. To solve it, a low complexity distributed UA algorithm is proposed. The results demonstrate that the proposed algorithm achieves higher throughput than the max reference signal received power (RSRP) and max signal-to-interference-plus-noise ratio (SINR) UAs. It also shows that increasing the number of antennas at the macro cell BS with more power consumption, the throughput continues to increase by using the proposed algorithm, compared to the decrease in throughput by using the existing ones. Increasing the number of mmWave BSs, mmWave BS antennas or mmWave bandwidths can significantly improve the throughput. Compared with massive MIMO macro cells, mmWave small cells play a dominant role in enhancing the throughput of the networks due to the larger bandwidths.
机译:本文考虑了混合异构网络(HetNet),其中宏小区采用大规模多输入多输出(MIMO),小小区采用毫米波(MMWAVE)传输。我们假设所有基站(BSS)都仅由可再生能源提供动力。这些新兴技术的实现对用户协会(UA)具有显着影响。由此激励,我们制定用户协会问题,以最大化网络实用程序,而每个BS的功率成本不超过收获的能量。为了解决它,提出了一种低复杂性分布式UA算法。结果表明,所提出的算法比最大参考信号接收功率(RSRP)和最大信号到干扰 - 噪声比(SINR)UA更高的吞吐量。它还表明,通过使用所存在的算法,通过使用所提出的算法,吞吐量增加了宏小区BS处的天线数量,与吞吐量的降低继续增加。增加MMWAVE BS的数量,MMWAVE BS天线或MMWAVE带宽可以显着提高吞吐量。与大规模的MIMO宏观小区相比,MMWAVE小型电池在提高由于带宽越大的增加网络的吞吐量方面发挥着主导作用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号