Published: 16 April 2017 16 April 2017
"TDD (Time Division) Massive MIMO represents the only effective implementation of Massive MIMO at the frequency bands under consideration."!? So says Professor Erik Larssen, a leading researcher at Linkoping University in Sweden. Larsson blogged the controversial paper on April 4, the day after it was published at https://arxiv.org/pdf/1704.00623.pdf. The blog and the abstract of the paper is below.
On the other hand, China Telecom, China Unicom, Huawei, and ZTE have announced successful trials of FDD (Frequency Division) Massive MIMO. A joint press release by China Telecom and ZTE asserts the opposite: "The FDD Massive MIMO solution is predictable to be deployed in China Telecom in 2017." Obviously, I'm not qualified to judge engineers of that quality when they disagree. I'll do my best to explain the issues and direct you back to the principals.
The primary issue, as I understand it, is whether FDD overhead is inevitably too high for FDD to be practical. With line of sight (LOS), the two techniques appear to have similar results. Without decent Line of Sight. the new paper reports a significant difference.
Massive MIMO requires constantly updated Customer State Information (CSI.) The transmitter needs constantly updated receiver location and capability to steer the many antennas. Larssen and colleagues have a theoretical model and now some test data that suggests FDD in many locations has too much overhead to be practical.
In the new paper, Massive MIMO Performance—TDD Versus FDD: What Do Measurements Say?, five academics report tests of TDD and four examples of FDD. The lead is Jose Flordelis, a student at Lund University. Three other authors are at Lund, Fredrik Rusek, Fredrik Tufvesson, and Ove Edfors, as well as Larsson of Linkoping. The two Swedish Universities, 400 kilometers apart, are important EU wireless centers.
In a previous paper, Larsson joined Emil Bjornson and Tom Marzetta to offer a theoretical model that came to a similar conclusion. One of their examples show TDD requires about 12.5% for CSI and FDD would have overhead four times as high,
The Chinese have upended many assumptions over the last ten years so I'll wait for more data.
Here are the description of the testing, the abstract, and the conclusion of the paper.
The measurements were acquired at a carrier frequency of 2.6 GHz, and a bandwidth of 50 MHz. A brief description of the two campaigns and the scenarios follows: • Campaign A. The UEs were located at the parking place outside the E-building of LTH, with the ULA mounted on top of the E-building, three floors above ground level. We consider five UE sites, denoted MS 1, . . . , MS 5. Sites MS 1 to MS 4 have mainly LOS propagation conditions to the BS, while site MS 5 experiences NLOS. At each site, several UE locations are measured. In this work, we consider three propagation scenarios, which are summarized in Table I as scenarios 1, 2, and 3. For further details on Campaign A, the reader is referred to . • Campaign B. The UEs were located in a courtyard of the E-building. The ULA was on a roof two floors above ground, while the 16 UEs were spread out at various positions in the courtyard. In this environment, the UEs experience LOS propagation conditions to the array, along with a number of strong scattered components caused by interactions with the walls, outdoor furniture, and vegetation. (The Ricean K-factor ,  is low compared to scenarios 1 and 3.) In this work, we consider three propagation scenarios, which are summarized in Table I as scenarios 4, 5, and 6. For further details on Campaign B, the reader is referred to .
There has been a long-standing debate on the relative performance between reciprocity-based (TDD) Massive MIMO and that of FDD solutions based on grid-of-beams, or hybrid beamforming architectures. The matter was, for example, the subject of a heated debate in the 2015 Globecom industry panel “Massive MIMO vs FD-MIMO: Defining the next generation of MIMO in 5G” where on the one hand, the commercial arguments for grid-of-beams solutions were clear, but on the other hand, their real potential for high-performance spatial multiplexing was strongly contested.
While it is known that grid-of-beams solutions perform poorly in isotropic scattering, no prior experimental results are known. This new paper: answers this performance question through the analysis of real Massive MIMO channel measurement data obtained at the 2.6 GHz band. Except for in certain line-of-sight (LOS) environments, theoriginal reciprocity-based TDD Massive MIMO represents the only effective implementation of Massive MIMO at the frequency bands under consideration.
Massive MIMO Performance—TDD Versus FDD: What Do Measurements Say?
Jose Flordelis, Student Member, IEEE, Fredrik Rusek, Member, IEEE, Fredrik Tufvesson, Fellow, IEEE, Erik G. Larsson, Fellow, IEEE, and Ove Edfors, Senior Member, IEEE Abstract—Downlink beamforming in Massive MIMO either relies on uplink pilot measurements—exploiting reciprocity and TDD operation, or on the use of a predetermined grid of beams with user equipments reporting their preferred beams, mostly in FDD operation. Massive MIMO in its originally conceived form uses the first strategy, with uplink pilots, whereas there is currently significant commercial interest in the second, grid-ofbeams. It has been analytically shown that in isotropic scattering (independent Rayleigh fading) the first approach outperforms the second. Nevertheless there remains controversy regarding their relative performance in practice. In this contribution, the performances of these two strategies are compared using measured channel data at 2.6 GHz. Index Terms—Massive MIMO, FDD, TDD, performance, channel measurements.
VI. CONCLUSIONS Using measured channels at 2.6 GHz, we have compared the performance of five techniques for DL beamforming in Massive MIMO, namely, fully-digital reciprocity-based (TDD) beamforming, and four flavors of FDD beamforming based on feedback of CSI (D-GOB, H-GOB, D-SUB, and H-SUB). The central result is that, while FDD beamforming with predetermined beams may achieve a hefty share of the DL sum-rate of TDD beamforming, performance depends critically on the existence of advantageous propagation conditions, namely, LOS with high Ricean factors. In other considered scenarios, the performance loss is significant for the non reciprocity-based beamforming solutions. Therefore, if robust operation across a wide variety of propagation conditions is required, reciprocity based TDD beam forming is the only feasible alternative.