Design of mmwave massive MIMO cellular systems

Design of mmwave massive MIMO cellular systems Abbas Kazerouni and Mainak Chowdhury Faculty mentor: Andrea Goldsmith Wireless Systems Lab, Stanford University March 23, 2015

Future cellular networks Higher data rates More users Greater energy efficiency

Future cellular networks Higher data rates More users Greater energy efficiency Enablers for next generation cellular More spectrum (mmwave) Efficient frequency reuse/coexistence (massive MIMO)

Properties of mmwave and massive MIMO mmwave Massive amount of spectrum Higher data rates Large attenuation from path loss and shadowing Stringent ADC requirements High speed baseband processor requirements massive MIMO High directivity Large antenna array size Channel estimation challenges

mmwave massive MIMO in cellular Benefits Directivity of massive MIMO compensates for high mmwave attenuation, reduces multipath and multiuser interference mmwave frequencies reduce the size required for massive MIMO antenna arrays Some key challenges in mmwave massive MIMO Channel estimation ADC requirements and baseband complexity Massive MIMO testbed, Lund University, Globecom 2014 Hybrid beamforming architecture for mmwave, Samsung, Globecom 2014

Our proposed work addresses these key challenges

Pilot contamination Channel estimation Reusing the pilots in other cells results in interference In the infinite antenna regime, this is the only limiting factor on the capacity 1 1 Marzetta, Thomas L. Noncooperative cellular wireless with unlimited numbers of base station antennas. IEEE Trans. on Wireless Commun. 9.11 (2010): 3590-3600.

Pilot contamination in small cells Cell size reduction mitigates pilot contamination 2 ( ) α,sir = 1 R 2 ρ Worst Case Capacity (bits/sec/hz) 60 50 40 30 20 10 α = 2 α = 4 α = 4 α = 8 0 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 User Density ρ (person/m 2 ) In the infinite antenna regime, cell size reduction increases the user density and the capacity of each user 2 A. Kazerouni, F. J. Lopez-Martinez, A. Goldsmith, Increasing capacity in massive MIMO cellular networks via small cells, IEEE Globecom workshop, 2014

Pilot contamination for moderate array sizes With non-infinite antenna arrays, the effect of noise and intra-cell interference is not negligible cross correlation between columns of H 10 1 10 2 10 3 10 1 10 2 10 3 10 4 10 5 10 6 number of antennas y = Hx + ν, H R n 4

Do we need channel estimation at all? Short answer Not always, and not estimating the channel may also address the second key challenge about baseband processing complexity 3 M. Chowdhury, A. Manolakos, A. Goldsmith, Coherent versus noncoherent massive SIMO systems: which has better performance?, IEEE ICC 2015 4 M. Chowdhury, A. Manolakos, A. Goldsmith, Noncoherent energy-based communications for the massive SIMO MAC, under revision, IEEE Trans. Info. Theory, 2015

Do we need channel estimation at all? Short answer Not always, and not estimating the channel may also address the second key challenge about baseband processing complexity Noncoherent architecture for a multiuser SIMO system Coherent phase reference may not be necessary 3 2 n Tx Rx to energy based baseband processor Analog or hybrid analog/digital architectures reduce demands on phase recovery circuits, ADCs, etc. 4 3 M. Chowdhury, A. Manolakos, A. Goldsmith, Coherent versus noncoherent massive SIMO systems: which has better performance?, IEEE ICC 2015 4 M. Chowdhury, A. Manolakos, A. Goldsmith, Noncoherent energy-based communications for the massive SIMO MAC, under revision, IEEE Trans. Info. Theory, 2015

Do we need channel estimation at all? Short answer Not always, and not estimating the channel may also address the second key challenge about baseband processing complexity Noncoherent architecture for a multiuser SIMO system Coherent phase reference may not be necessary 3 2 n Tx Rx to energy based baseband processor Analog or hybrid analog/digital architectures reduce demands on phase recovery circuits, ADCs, etc. 4 Energy efficiency 3 M. Chowdhury, A. Manolakos, A. Goldsmith, Coherent versus noncoherent massive SIMO systems: which has better performance?, IEEE ICC 2015 4 M. Chowdhury, A. Manolakos, A. Goldsmith, Noncoherent energy-based communications for the massive SIMO MAC, under revision, IEEE Trans. Info. Theory, 2015

Noncoherent architectures for different channel models MISO, MIMO channels Can massive antenna arrays at transmitter be exploited without channel state information (CSI)? Wideband Number of channel coefficients to be estimated is large Multi-carrier energy based system achieves same capacity scaling behavior as coherent systems 5 How do single carrier implementations compare with a multi-carrier implementation? 5 M. Chowdhury, A. Manolakos, F. Gomez-Cuba, E. Erkip, A. Goldsmith, Capacity scaling in noncoherent wideband massive SIMO systems, IEEE ITW, Jerusalem, 2015

Validation of theory on empirical channel models Empirical channel models for mmwave mmwave channel models still being developed Gains depend on models used Correlation in Rx antenna reduces capacity due to loss in diversity uncorrelated ergodic capacity 8 6 4 correlated ergodic capacity 8 6 4 10 1 10 1.5 10 2 10 2.5 number of antennas 10 1 10 1.5 10 2 10 2.5 number of antennas

Validation of theory on empirical channel models Empirical channel models for mmwave mmwave channel models still being developed Gains depend on models used Correlation in Rx antenna reduces capacity due to loss in diversity uncorrelated ergodic capacity 8 6 4 correlated ergodic capacity 8 6 4 10 1 10 1.5 10 2 10 2.5 10 1 10 1.5 10 2 10 2.5 number of antennas number of antennas How do results change for real life mmwave channels? How does correlation affect general MIMO transmission?

Thanks for your attention

Thanks for your attention Questions?