Interference in Finite-Sized Highly Dense Millimeter Wave Networks Kiran Venugopal, Matthew C. Valenti, Robert W. Heath Jr. UT Austin, West Virginia University Supported by Intel and the Big- XII Faculty Fellowship program
Wearable communication networks u The next frontier for wireless communications ª Multiple devices in and around human body ª Low-rate fitness monitors to high-rate infotainment devices u Critical challenge ª Supporting Gbps per user in dense environments ª Effective operation in finite areas like trains, trolleys, or buses [1] http://www.bombardier.com/en/transportation/products-services/railvehicles/metros.html [2] Smart wearable devices: Fitness, healthcare, entertainment & enterprise 2013-2018, Juniper Research, Oct. 2013. 2
MmWave as solution for wearable networks USA 1 Japan 2 Australia 3 Europe 4 Max transmit power : 500 mw Max EIRP : 43 dbm Max output power: 10 mw Max bandwidth: 2.5 GHz; Max antenna gain: 47 dbi Max output power: 10dBm Max EIRP: 51.8 dbi Max transmit power : 20 mw Max EIRP : 40 dbm 57 GHz 59 GHz 64 GHz 66 GHz Several GHz of spectrum available for worldwide operation 0 u High bandwidth and reasonable isolation Robert W. Heath Jr. (2015) u Compact antenna arrays to provide array gains via beamforming u Commercial products already available: IEEE 802.11ad, WirelessHD 1 47 CFR 15.255; 2 ARIB STD-T69, ARIB STD-T74; 3 Radiocommunications Class License 2000; 4 CEPT : Official journal of the EU; 3
Motivating prior work u Stochastic geometry models for mmwave cellular networks [1]-[3] ª Infinite spatial extent and number of nodes ª Did not consider people as a source of blockage u Performance analysis for finite ad-hoc networks [4] ª Does not include directional antennas or blockage u Self-blockage model for mmwave [5] ª Considers a 5G cellular system ª User's own body blocks the signal, not other users [1] T. Bai and R. W. Heath Jr., Coverage and rate analysis for millimeter wave cellular networks, IEEE Trans. Wireless Comm., 2014. [2] S. Singh, M. N. Kulkarni, A. Ghosh, and J. G. Andrews, Tractable model for rate in self-backhauled millimeter wave cellular networks, online [3] T. Bai, A. Alkhateeb, and R. W. Heath Jr., Coverage and capacity of millimeter-wave cellular networks, IEEE Commun. Magazine, 2014. [4] D. Torrieri and M. C. Valenti, The outage probability of a finite ad hoc network in Nakagami fading, IEEE TCOM, 2012. [5] T. Bai and R. W. Heath Jr., Analysis of self-body blocking effects in millimeter wave cellular networks, in Proc. Asilomar 2014. 4
What is different for mmwave wearable networks? Receiver Interferers Blocked 2D geometry u Finite number of interferers in a finite network region ª Realistic assumption for the indoor wearable setting w/ mmwave ª Fixed/random location of interferers (extended in journal version) u Blockages due to other human bodies (can be extended to pets) u Both interferer and blockage associated with a user 5
Contributions u Model interferers as also potential blockages Interferer as well as blockage u Analyze SINR distribution and rate ª Finite-sized mmwave-based wearable networks ª Conditioned on a fixed location for the interferers Receiver u Assess impact of antenna parameters on performance ª Factor in array size and gain ª Incorporate antenna directivity and orientation 6
SYSTEM MODEL 7
Modeling antenna pattern using a sectored antenna Number of antenna elements Beamwidth θ Main- lobe gain G Side- lobe gain g u Use a 2D sectored antenna model to simplify the analysis ª Parameterize via a uniform planar square array w/ half-wavelength spacing u Incorporates omni- direcjonal antennas as a special case ª = 1 à omni-directional antenna, G = g = 1 ª Of interest for inexpensive wearable 8
Network topology R i X i φ i Reference Rx Reference Tx Interfering Tx Finite region u Finite sized network region, area =, users u One interferer per user transmits at a time u ª interferers + reference transmitter-receiver pair, location of transmitters relative to reference receiver 9
Modeling human body blockages X i Y i Reference Rx Reference Tx Interfering Tx u Associate diameter W circle with each user denoted Y i u Determine blocking cone for each Y i u X i blocked if it falls in one of the blocking cones u Assume Y i does not block X i, i.e., no self-blocking 10
SIGNAL MODEL 11
Received signal model Reference Rx Reference Tx Interfering Tx Blockage associated with interfering Tx NLOS link LOS link u h i - Nakagami fading with parameter m i from X i u Link is NLOS if blocked and LOS otherwise m i = m N m i = m L 12
Path-loss model and power gains Reference Rx θ r Rx gain G r R i X i Reference Tx Interfering Tx φ 0 φ i Rx gain g r u - path-loss exponent from X i : for LOS, for NLOS u Define Tx power of X i Ref. receiver s main-lobe points towards X i Captures path loss and Rx orientation 13
Signal from reference transmitter Reference Rx Reference Tx R 0 u h 0 Nakagami fade gain from reference with parameter m 0 u Assume that there is always LOS communication u Reference Tx is within the main beam of the reference Rx 14
Relative transmit power Gain G t w.p. (θ t /2π) θ t Transmit antenna at X i Gain g t w.p. (1 - θ t /2π) u X i transmits with probability p t (Aloha-like medium access) u X i points its main-lobe in a (uniform) random direction u Define Probability that ref. receiver is within main-lobe of X i Captures p t and random Tx orientation 15
SINR and ergodic spectral efficiency Evaluate CCDF of SINR Derive ergodic spectral efficiency u SINR is Noise power normalized by P 0 16
CCDF of SINR u SINR coverage probability for a given threshold 17
CCDF of SINR u SINR coverage probability for a given threshold where 18
NUMERICAL RESULTS 19
Setting Receiver at center u 5 X 9 rectangular grid u Separation between nodes = 2R 0 u No reflection from boundaries Receiver at a corner Parameter s Value R 0 1 m L 4 m N 2 α L 2 α N 4 W 1 σ 2-20 db K 44 u All nodes transmit with same P i 20
CCDF of SINR: Dependence on p t Omni Tx and Rx Receiver at the center u Higher transmission probability p t results in smaller SINR u Similar trend with other antenna configurations 21
Spectral efficiency for different antenna configurations p t = 0.1 N t =N r =16 Receiver at the center N t =N r =1 Significant benefits to beamforming 22
Effect of receive antenna orientation Robert W. Heath Jr. (2015) Receiver at the center Receiver at a corner p t = 0.7 N t = N r = 16 Orientation of RX is more important in the corner 23
Rate trends with N t and N r Assume 2.16 GHz BW of IEEE 802.11ad N t N r Ergodic spectral efficiency (bits/s/hz) Rate (Gb/s) Receiver at center Receiver at a corner Receiver at center Receiver at a corner 1 1 0.499 1.063 1.08 2.30 p t = 1 1 4 0.797 1.405 1.72 3.03 1 16 1.757 2.087 3.80 4.51 4 1 2.449 4.046 5.29 8.74 4 4 3.210 5.072 6.93 10.96 4 16 5.437 7.078 11.74 15.29 16 1 3.618 5.027 7.81 10.86 16 4 4.635 6.396 10.01 13.82 16 16 6.952 8.434 15.02 18.22 Gigabit throughputs are achieved even with a single transmit and receive antenna 24
Contour plot of ergodic spectral efficiency Robert W. Heath Jr. (2015) p t = 0.5 Receiver at the center *Units in bits/s/hz 25
Concluding remarks u MmWave can provide Gbps data rates to wearables u Performance varies based on location and orientation ª Corner users can point their antenna away from the crowd ª Center users suffer more neighboring interference u Wearable networks offer many interesting features for future work ª Interferers with random locations ª Self-body blocking models ª 3D link orientation 26
QUESTIONS? 27