1 From Adaptive Antennas to MIMO Systems and Beyond Yasutaka Ogawa Hokkaido University, Sapporo, Japan February 2016
2 Concept of Adaptive Antenna Control of the array pattern q #1 x () t 1 10 Interference Desired Signal #2 #N x () t 2 x () N t w 1 w 2 S Array Output N yt () wx i i() t i1 0-10 -20-30 -40 Weight Control w -50 N 0 30 60 90 120 150 180 [deg.]
3 History of Adaptive Antenna Research 1950s Retrodirective array Self-steering array 1960s Sidelobe canceller MSN adaptive array MMSE adaptive array Beamforming Interference suppression by null steering Anti-jamming for military use Commercial applications were NOT considered
4 Applications to Commercial Mobile Radio What benefits? Multipath suppression - High-speed transmission Range extension Interference reduction - Lower cell repeat pattern - Same channel reuse (SDMA) Efficient use of frequency
5 Secret History behind the Research Field Strong Objection to Adaptive Antennas in the Research Community
6 Objection 1 No Need for Adaptive Antennas An ultra low sidelobe antenna can reduce interference Interference Desired Signal Interference
7 Objection 2 People who do not know radio waves study adaptive antennas TX Side Channel RX Side Dual Polarized Communication Model Y. Ogawa, et al., Basic studies on dual polarized communications in a land mobile radio system, IEICE Technical Report, AP88-15, June 1988.
Objection 2 cont d 8 RX Structure XPIC Cross Polarization Interference Canceler
9 Increased Interest in Applications to Mobile Radio Project in Europe Technology in Smart antennas for the UNiversal Advanced Mobile Infrastructure (TSUNAMI) (1994.1 1995.12) University of Bristol, Aalborg University, Alcatel SEL, Hagenuk GMBH, Hokkaido University Group Y. Ogawa, et al., Behaviors of an LMS adaptive array for multipath fading reduction, IECE Trans., vol. E67, no. 7, pp. 395-396, July 1984.
10 SDMA with Multibeam Adaptive Antenna - Multibeam adaptive antenna can separate multiple-user signals - Accommodation of multiple users in the same frequency band in the same cell - Space Division Multiple Access (SDMA) Pattern ユーザ1for のパターン user 1 ユーザ User 11 Basestation 基地局 ユーザ User 2 ユーザ Pattern 2のパターン for user 2
14 Commercial PHS-SDMA Basestation First commercial SDMA in the world
15 Emergence of MIMO Systems - Multiple antennas at both of a transmitter and a receiver - Multipath-rich environments - Each channel is contribution of multipath signals - Correlations between channels are low #1 #1 TX #2 #2 RX
Why MIMO? (1) 16 Transmit Power P According to Shannon, Transmit Power 2P S N 2S N 2 2 log 1 bps/hz log 1 S C N S S N N 2 2 2 log 1 2 log S C N S N C 1
Why MIMO? (2) 17 Transmit Power 2P P P S N S N C S 2log2 1 N S 2log2 N 2C A MIMO system generates parallel channels in a spatial domain in multipath-rich environments, and increases channel capacity Transmitter Receiver
18 Multipath Signal: Our Friend or Enemy? Generating multiple channels: Good! Causing fading: No Good! Maximum Eigenvalues of HH H Minimum Eigenvalues of HH H 1 1 Cumulative Distribution 0.8 0.6 0.4 0.2 4x20 4x100 4x4 Cumulative Distribution 0.8 0.6 0.4 0.2 4x4 4x20 4x100 0-30 -20-10 0 10 20 30 Amplitude [db] 0-30 -20-10 0 10 20 30 Amplitude [db] Almost no fading for maximum eigenvalue channels Fading depth is small even for minimum eigenvalue channels in MIMO systems with many antennas
19 First Paper Dealing with the MIMO Concept Jack H. Winters, On the Capacity of Radio Communication Systems with Diversity in a Rayleigh Fading Environment, IEEE Journal on Selected Areas in Communications, vol. SAC-5, no. 5, pp. 871-878, June 1987. the communication channels between multiple transmit and/or receive antennas can have low cross correlation even when the transmit or receive antennas are closely spaced. 上記論文の図 6 を貼り付ける Fig. 6. Radio system consisting of two users,
20 First Paper Dealing with the MIMO Concept cont d Optimum Transmitter/Receiver Processing The total normalized capacity is given by I s = log 2 (1 + i P i ) The P i s that maximize I s can be found by using the water fill analogy I noticed the paper, but did not recognize the importance and significance of it. This is one of my biggest regrets.
21 Key Technologies for 5G Cellular Network Massive MIMO utilizing a very high number of antennas Millimeter wave with an enormous amount of spectrum A successful marriage of massive MIMO and millimeter waves may take on a considerably different form F. Boccardi, R.W. Heath Jr., A. Lozano, T.L. Marzetta, and P. Popovski, Five Disruptive Technology Directions for 5G, IEEE Commun. Mag., vol. 52, no. 2, pp. 74-80, Feb. 2014.
22 Hybrid Beamforming for Massive MIMO Analog Beamformer RF AD/DA RF AD/DA RF AD/DA RF AD/DA Digital Beamformer Reasonable structure Low complexity Beamforming gain available for pilot
23 Analog Beamformers Multibeam Phased Array (Full Array, Subarray) Butler Matrix Lens Antenna Dielectric 4x4 Buttler Matrix
24 Beam Selection in an Analog Multi-Beamformer Fast beam selection is important in an analog multi-beamformer Example: - Beamformer with a 64x64 Butler Matrix and 4 RF units - Search a port with the maximum output power of a pilot Antennas #1 #2 #3 #64 64 x 64 Butler Matrix Ports #1 #2 #3 #64 RF Unit #1 RF Unit #2 RF Unit #3 RF Unit #4
25 64x64 Butler Matrix Beamformer 64 orthogonal beams realized by a 64x64 Butler Matrix An appropriate beam toward a user terminal must be selected out of the 64 beams
26 Beam Selection in a Butler Matrix Beamformer 16 Measurements are needed if all the port powers are measured １ 2 3 4 5 6 7 8 9101112 13 14 15 16
27 Efficient Beam Selection (1) 4 Broad beams are formed with 4 antennas and a 4x4 Butler Matrix S. Yuki, Y. Ogawa, T. Nishimura, and T. Ohgane, A Study on Beam Selection in High Frequency Band Analogue Beamformer, IEICE Technical Report, RCS2015-88, June 2015.
28 Efficient Beam Selection (2) The terminal direction is roughly estimated with the 4 antennas
29 Efficient Beam Selection (3) More accurate terminal direction is estimated with the 16 antennas and 16x16 Butler Matrix
30 Efficient Beam Selection (4) Appropriate beam for the 16 antennas is selected out of the 4 beams
31 Efficient Beam Selection (5) Appropriate beam for all the 64 antennas is selected out of the 4 beams
32 Efficient Beam Selection (6) Optimum beam is selected with the 3 measurements
33 For Further Development of MIMO Systems Digital Signal Processing Propagation Analysis Analog Technology