Spectrum efficiency has long been at the center of mobile communication research, development, and operation. Today it is even more so with the explosive popularity of the mobile Internet, social networks, and smart phones that are more powerful than our desktops used to be not long ago. The discovery of spatial multiplexing via multiple antennas in the mid-1990s has brought new hope to boosting data rates regardless of the limited bandwidth. To further realize the potential of spatial multiplexing, the next leap will be accounting for the three-dimensional real world in which electromagnetic waves propagate. In this article we discuss fundamentals and key technical issues in developing and realizing 3D multi-input multi-output technology for next generation mobile communications.

Communicating in the real world: 3D MIMO

Very recent studies showed that the area spectral efficiency (ASE) of downlink cellular networks will continuously decrease and finally crash to zero as the base station (BS) density increases toward infinity if the absolute height difference between BS antenna and user equipment antenna is larger than zero. Such a phenomenon is referred to as the ASE crash. We revisit this issue by considering optimizing the BS antenna downtilt in cellular networks. It is common to adjust antenna pattern to tune the direction of the vertical beamforming and thus increasing received signal power and/or reducing inter-cell interference power to improve network performance. This paper focuses on investigating the relationship between the BS antenna downtilt and the downlink network performance in terms of the coverage probability and the ASE. Our results reveal an interesting find that there exists an optimal antenna downtilt to achieve the maximum coverage probability for each BS density. Numerically solvable expressions are derived for such optimal antenna downtilt, which is a function of the BS density. Our numerical results show that after applying the optimal antenna downtilt, the network performance can be significantly improved, and hence the ASE crash can be delayed by nearly one order of magnitude in terms of the BS density. Our results also give guidance on setting the optimum downtilt angle to maximize network performance given a fixed BS density.

Optimal Base Station Antenna Downtilt in Downlink Cellular Networks

From very recent studies, the area spectral efficiency (ASE) performance of downlink (DL) cellular networks will continuously decrease and finally to zero with the network densification in a fully loaded ultra-dense network (UDN) when the absolute height difference between a base station (BS) antenna and a user equipment (UE) antenna is larger than zero, which is referred as the ASE Crash. We revisit this issue by considering the impact of the BS antenna downtilt on the downlink network capacity. In general, there exists a height difference between a BS and a UE in practical networks. It is common to utilize antenna downtilt to adjust the direction of the vertical antenna pattern, and thus increase received signal power or reduce inter-cell interference power to improve network performance. This paper focuses on investigating the relationship between the base station antenna downtilt and the downlink network capacity in terms of the coverage probability and the ASE. The analytical results of the coverage probability and the ASE are derived, and we find that there exists an optimal antenna downtilt to achieve the maximal coverage probability for each base station density. Moreover, we derive numerically solvable expressions for the optimal antenna downtilt, which is a function of the base station density. Our theoretical and numerical results show that after applying the optimal antenna downtilt, the network performance can be improved significantly. Specifically, with the optimal antenna downtilt, the ASE crash can be delayed by nearly one order of magnitude in terms of the base station density.

In 3GPP LTE-A, Coordinated Multi-Point (CoMP) is adopted to enhance the transmission rates of edge users To maximize the total downlink throughput of all edge users, it is crucial to properly determine the set of simultaneously served users in each physical resource block (PRB) and the cooperative base stations (BSs) for each scheduled user, as well as the transmit power of the BSs Based on the reference signal receiving power (RSRP) of each edge user, we first propose two simple and integrated transmission scheduling algorithms, one distributed and the other centralized, to choose cell-edge users and cooperative BSs in each PRB With the scheduling results, the classic Water-Filling (WF) algorithm is carried out over all PRBs at each BS to get an initial single cell power allocation To take the interference among different cooperative BS sets into account, we further formulate a non-cooperative power allocation game to adjust the initial power allocation for interference coordination, where the initial power allocation provides the strategy space of the game for each BS This increases the total downlink throughput of edge users over all BSs We prove that the game has a unique Nash Equilibrium (NE), and design an algorithm to find the NE Performance gain is then demonstrated through extensive simulation studies

Transmission Scheduling and Game Theoretical Power Allocation for Interference Coordination in CoMP

Machine learning will play a major role in handling the complexity of future mobile wireless networks by improving network management and orchestration capabilities. Due to the large number of parameters that can be monitored and configured in the network, collecting and processing high volumes of data is often unfeasible or too expensive at network runtime, which calls for taking resource management and service orchestration decisions with only a partial view of the network status. Motivated by this fact, this paper proposes a transfer learning framework for reconstructing the radio map corresponding to a target antenna tilt configuration by transferring the knowledge acquired from another tilt configuration of the same antenna, when no or very limited measurements are available from the target. The performance of the framework is validated against standard machine learning techniques on a data set collected from a 4G commercial base stations. In most of the tested scenarios, the proposed framework achieves notable prediction accuracy with respect to classical machine learning approaches, with a mean absolute percentage error below 8%.

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Transfer Learning for Tilt-Dependent Radio Map Prediction

The benefits of horizontal beamforming in cellular networks are well unterstood, and the technology is already used in commercial products. Recently, vertical beamforming (basically a user specific downtilt (DT)) receives a lot of attention as well. However, available channel models do not allow for an accurate simulation of this transmission scheme. This publication investigates the impact of antenna DT in a typical urban area using field trials. Two models are presented and compared with measurement data in order to study their value and limitations for the evaluation of vertical beamforming, which is an important basis for planning and deploying of such schemes in order to increase cellular downlink (DL) throughput.

Field trial evaluation of UE specific antenna downtilt in an LTE downlink

This paper presents measurement results for coordinated multi-point downlink transmissions as Long Term Evolution - Advanced concept from a cellular test bed in Dresden, Germany. At first, a description of the real-time prototyping system and its signal processing introduces the major modifications from the existing 3GPP-LTE standard. Then, the cellular propagation and measurement environment of the test bed is characterized. Various spatial setups are compared in conjunction with cooperative and non-cooperative base stations as well as cell-center and cell-edge scenarios. Finally, results concerning the geometry factor, time difference of arrivals and spectral efficiencies complete this field trial.

Joerg Holfeld

Papers

Field trial evaluation of UE specific antenna downtilt in an LTE downlink

Field trial results for CoMP downlink transmissions in cellular systems