Multi-cell massive MIMO network optimization towards power consumption in suburban scenarios

In this paper, we propose a simulation-based method to design low power multi-cell multi-user massive MIMO network by optimizing the positions of the base stations. Two realistic outdoor suburban areas have been considered in Ghent, Belgium (Europe) and Kinshasa, the Democratic Republic of Congo (Africa), in which the power consumption, the energy efficiency, the network capacity and the multiplexing gain are investigated and compared with LTE networks. The results of the simulations demonstrated that massive MIMO networks provide better performance in the crowded scenario where user's mobility is relatively low. A massive MIMO BS consumes 5-8 times less power than the LTE networks, with a pilot reuse pattern of 3 that helps obtaining a good tradeoff between the higher bit rate requested and the low power requirements in cellular environment

Multi-objective optimization of massive MIMO 5G wireless networks towards power consumption, uplink and downlink exposure

Featured Application The proposed method serves for the network planning of massive Multiple Input Multiple Output (MIMO) based 5G networks. This will be beneficial for the mobile network operators who aim to deploy wireless networks that are cost-effective and electromagnetic (EMF) -aware while providing maximal coverage for the users. Abstract The rapid development of the number of wireless broadband devices requires that the induced uplink exposure be addressed during the design of the future wireless networks, in addition to the downlink exposure due to the transmission of the base stations. In this paper, the positions and power levels of massive MIMO-LTE (Multiple Input Multiple Output-Long Term Evolution) base stations are optimized towards low power consumption, low downlink and uplink electromagnetic exposure and maximal user coverage. A suburban area in Ghent, Belgium has been considered. The results show that the higher the number of BS antenna elements, the fewer number of BSs the massive MIMO network requires. This leads to a decrease of the downlink exposure (-12% for the electric field and -32% for the downlink dose) and an increase of the uplink exposure (+70% for the uplink dose), whereas both downlink and uplink exposure increase with the number of simultaneous served users (+174% for the electric field and +22% for the uplink SAR). The optimal massive MIMO network presenting the better trade-off between the power consumption, the total dose and the user coverage has been obtained with 37 64-antenna BSs. Moreover, the level of the downlink electromagnetic exposure (electric field) of the massive MIMO network is 5 times lower than the 4G reference scenario

Optimal low-power design of a multicell multiuser massive MIMO system at 3.7 GHz for 5G wireless networks

Massive MIMO techniques are expected to deliver significant performance gains for the future wireless communication networks by improving the spectral and the energy efficiencies. In this paper, we propose a method to optimize the positions, the coverage, and the energy consumption of the massive MIMO base stations within a suburban area in Ghent, Belgium, while meeting the low power requirements. The results reveal that massive MIMO provides better performances for the crowded scenario where users' mobility is limited. With 256 antennas, a massive MIMO base station can simultaneously multiplex 18 users at the same time-frequency resource while consuming 8 times less power and providing 200 times more capacity than a 4G reference network for the same coverage. Moreover, a pilot reuse pattern of 3 is recommended in a multiuser multicell environment to obtain a good tradeoff between the high spectral efficiency and the low power requirement

Towards versatile access networks (Chapter 3)

Compared to its previous generations, the 5th generation (5G) cellular network features an additional type of densification, i.e., a large number of active antennas per access point (AP) can be deployed. This technique is known as massive multipleinput multiple-output (mMIMO) [1]. Meanwhile, multiple-input multiple-output (MIMO) evolution, e.g., in channel state information (CSI) enhancement, and also on the study of a larger number of orthogonal demodulation reference signal (DMRS) ports for MU-MIMO, was one of the Release 18 of 3rd generation partnership project (3GPP Rel-18) work item. This release (3GPP Rel-18) package approval, in the fourth quarter of 2021, marked the start of the 5G Advanced evolution in 3GPP. The other items in 3GPP Rel-18 are to study and add functionality in the areas of network energy savings, coverage, mobility support, multicast broadcast services, and positionin

Combined ray-tracing/FDTD and network planner methods for the design of massive MIMO networks

The design of a massive MIMO network requires a channel model that captures the Spatio-temporal dimensions of the propagation environment. In this paper, we propose a novel method combining Hybrid Raytracing - Finite difference time domain (FDTD) and network planner tools to address this requirement. This method provides accurate and realistic EMF exposure models for the design of a massive MIMO network. Using this method, we proceed with the optimization of the BS's locations under the low power consumption and low EMF exposure constraints. Assuming equal preference of the optimization objectives, the simulations show that the uplink localized 10g dose appears to be the dominant factor of the localized 10g EMF exposure. Moreover, a massive MIMO network designed to serve 224 simultaneous active users at the same time-frequency resource is subject to an increase of the total whole-body dose (2 times higher in downlink and +18% in uplink), compared to a design with 14 active users. However, in the same conditions, the downlink localized 10g dose reduces (20 times lower) whereas the uplink localized 10g dose increases (+23%) in comparison with the scenario with fewer users (14). Besides, the electromagnetic field strength in all locations obtained with this new method is 2 times weaker compared to a 4G LTE network, while complying with the international guidelines