The Vault

System Level Performance of Millimeter-wave Access Link for Outdoor Coverage
Research Paper / Feb 2014

System Level Performance of Millimeter-wave Access Link for Outdoor Coverage Mohamed Abouelseoud and Gregg Charlton InterDigital, King of Prussia, PA 19406, USA Email:mohamed.abouelseoud@interdigital.com, gregg.charlton@interdigital.com Abstract— The increased demand on data and the scarcity of available bandwidth motivate research for new technologies beyond 4G. In this paper we provide a system level study of a new cellular architecture that incorporates millimeter wave technology (60 GHz) for the access link. A system level simulation is carried out for a university campus and an urban environment and the sensitivity to various design parameters has been studied. The objective of such a system is to provide up to 500X the wireless network capacity that is delivered today without a significant increase in energy or deployment costs. I. INTRODUCTION The exponential growth of data demand, increased use of smart-phones and tablets and the emergence of new wireless applications with rich multimedia content create a need for a new synergetic strategies capable delivering this huge demand. The use of small cells increases the spacial reuse and reduces transmit power which leads to greater throughput in the network. The main downside is the need for interference management and the cost associated with deploying many small cell base stations. Another viable solution is to explore higher frequency bands where huge amounts of spectrum are available with potentially very affordable licensing costs. The bandwidth of the 60 GHz unlicensed spectrum alone is about 7 GHz (depending on country), which is more than all available bandwidth in the traditional cellular spectrum. The availability of this bandwidth opens the door for new applications that need higher network capacity and power savings by trading spectrum for power and using simpler waveforms. There has been a lot of work in both academia and industry investigating the use of 60 GHz carriers, for example [1]– [4] for indoor coverage and [5] for outdoor coverage. There have been other activities in the industrial standards as well, for example, IEEE 802.11ad, WirelessHD, ECMA-387, IEEE 802.15.3c and the Wireless Gigabit Alliance (WiGig). There are, however, many challenges associated with the 60 GHz band. The high molecular oxygen absorption is a concern for long links. Another limiting factor is due to the 40 dBm FCC EIRP limit. Furthermore, the 60 GHz band is unlicensed, making it difficult to predict how well different radio access technologies (RATs) may coexist and if operators will consider the band reliable enough. Another big concern is the propagation channel itself. The millimeter wave (mmW) carriers have near optical properties with high penetration Fig. 1: The proposed system architecture losses, high reflection losses, and little diffraction, leading to line of sight (LOS) dominated coverage. It is expected that the mmW base stations (mBs) to be deployed in heavily crowded areas where the LOS between the mB and the user equipment (UE) can be easily blocked. The proposed architecture, Figure 1, includes new small mmW base stations (mBs) that are overlaid on a cellular network. The mBs are denser than the eNBs and self-backhaul using a mmW MESH network to the eNB (or other wired access). The phased array antennas create narrow steerable beams that provide links with low interference to both access links and backhaul transmissions. Each such node is also connected to a coverage network on a traditional carrier (e.g., a cellular network) to provide mobility management, security, and other control functions. In this paper we provide a system level study for the outdoor access link of a mmW system. We simulate the physical layer of such system and carry out sensitivity studies on multiple design parameters. Deployments in a university campus and an urban area are studied and we evaluate the effect of the directivity of the Tx and Rx antenna, the density of the mBs, modulation schemes, system threshold, inter-site distance and mB location placement. II. SIMULATOR DESIGN The simulator comprises two main modules. The first is the cell planning tool, WINPROP from AWE Communica- tions [6], which is capable of creating outdoor scenarios in which the user is able to specify the RF properties of the various building materials and vegetation areas. Based on ray978-1-4673-5939-9/13/$31.00 ©2013 IEEE978-1-4673-5939-9/13/$31.00 ©2013 IEEE2013 IEEE Wireless Communications and Networking Conference (WCNC): PHY2013 IEEE Wireless Communications and Networking Conference (WCNC): PHY4146 (a) 3D view (b) mBs deployments Fig. 2: University college campus mBs deployments tracing, the tool determines the delay, signal strength, and type of interaction the path rays encounter from transmitter to receiver for each path arriving at a user-defined grid point while taking the transmit antenna pattern into account. The second module is a system simulator written in Mat- lab. This tool uses data from WINPROP to create channel models that are used to estimate the throughput achieved by UEs. The UEs locations are randomly drawn from the set of pre-generated grid points. Each dropped UE is randomly oriented in azimuth and elevation.The simulator models the impacts of the transmit power, inter-cell interference, receive antenna gain, modulation scheme, scheduler parameters, etc. The statistics are then collected to generate an estimate of the overall network performance. A. Channel Model The aforementioned WINPROP tool is configured to run in a deterministic fashion in which individual rays (LOS, reflected, and diffracted) are traced between each transmitter and the entire set of user-defined grid points. The signal strength, delay and angle of arrival for each ray are function of the re- flection and diffraction angles, building materials, propagation model, transmit antenna pattern etc. The received power/delay combination allows for the creation of a tapped delay profile. A fading profile is applied to each of the identified rays to capture the fast fading environment. The fading profile follows a Rician distribution rather than a Rayleigh distribution with k- factor of 10 because of the LOS characteristics of the channel. B. Tx and Rx Antenna Design and Beam Assignments To generate the mB’s desired antenna patterns we use a uniform rectangular planar phase array (URA) while varying the number of elements. The UE is associated to one of the possible beams that the array could generate. Each URA is assumed to cover 90◦ in azimuth. The design parameters for the tested patterns are given in Table I. The gain of the Rx antenna depends on the received ray AoA. An ideal omni- directional antenna and a directional antenna have been tested. The omni-directional antenna has a uniform 0 dBi gain in all directions while the directional antenna is a 4x4 URA with element spacing equal to half the wavelength. The antenna No of Beams Sep. Angle (◦) No of Ele- ments (NxN) Gain (dBi) 3dB beam- width (◦) Crossover Point (◦) Spacing (λ) Crossover Point Gain (dB) 5 18 12 21.6 6.5 8.9 0.32 -5.93 7 12.86 16 24.1 4.75 6.5 0.33 -5.95 9 10 20 26 3.7 5 0.34 -5.81 TABLE I: Base station antenna patterns specification array generates 5 beams in the 0◦ elevation angle plane with approximately 60◦ beamwidth with overlap at the 3 dB point. This is equivalent to approximately 30◦ beam separation. A set of down-tilted beams and a set of up-tilted beams are used to form a 5x3 beam array. Also, back-to-back planar phased array antennas are used to cover the front and the back of the UE to provide coverage all around the UE. UE-mB association is a two stage process. In the first stage, the received power from all mBs antenna beams is measured at the UE location with a quasi-omni antenna pattern in the case where the UE antenna is directional, or an ideal-omni antenna if no directional antenna is used. The quasi-omni antenna pattern is just the pattern of a single element patch antenna which effectively constrains the possible pointing direction of the array. The mB array and corresponding beam providing the largest Rx power is selected. In the second stage (only for directional receive antennas), all possible Rx beams at the UE are varied to determine the best receive antenna pattern. C. Self Blockage It is assumed that the signal coming from the back side of the UE is attenuated by 40 dB. For an average blocker 175 cm tall and 60 cm wide holding the UE 30 cm away, the blocking angle is a 90◦ azimuth angle centered at the back of the UE and elevation angles between 62.8◦ and 90◦. D. SINR and Throughput Calculation After calculating the instantaneous SINR for the scheduled UEs, the SINR is mapped to its corresponding throughput. Shannon capacity formula provides an upper bound on per- formance where R = B log 2 (1 + SINR), B is the bandwidth and R is the achieved rate. A second method is to map SINR to throughput via a lookup table. We use tables based on LTE (QPSK, 16QAM and 64-QAM) [7] and also based on adaptive modulation and coding schemes from 802.11ad [8]. E. Default Simulation Parameters We consider 10 UE drops, each comprising 1000 samples (TTIs). The total number of UEs per drop is 50 which corresponds to a UE density of 730 UE/km2. A TTI duration is assumed to be 1 msec. The carrier frequency is 60 GHz. Following 802.11ad, a total of 2640 MHz bandwidth is used and divided into 512 sub-carriers of which 336 are used for data. The UE noise figure is 6 dB. Unless otherwise noted, Round Robin scheduling is used to distribute the resources4147 equally among the users and ideal omni-directional Rx An- tennas are used. The mB antenna’s down-tilt angle is 0◦ and mBs have an EIRP of 40 dBm. The mB’s height is 4 m and the UE’s height is 1.5 m. III. UNIVERSITY CAMPUS PERFORMANCE EVALUATION The studied campus shown in Figure 2 is an abstracted version of a large, public university that contains trees and buildings of various heights. Two proposed mB placement schemes are considered. The first relies on 4 mBs placed at the corners of the college campus with the intent that they provide coverage to the main quadrangle. The other has an additional 5th mB placed at the center of the quadrangle itself. Access link system performance is measured by the metrics of user throughput and total network throughput. A. Multiple mB Configurations Two mB deployment schemes are tested. The number of azimuth beams per array is varied from 5 to 9. The default tilt angle is set to 0◦. For the 9 beams/array case, two tilt angles were applied to the antenna arrays, 0◦ and −15◦. The EIRP is held constant for each mB antenna type so the improvement seen as one moves to narrower beams is not due to increased transmit power. Figures 3 and 4 show the user and the total cell throughput, respectively. The additional mB at the center of campus improves performance where the added interference does not overcome the SNR improvement and the frequency reuse gain. As expected, generally, narrower beams (7 vs. 5 beams/array) provide better performance since there is less likelihood of inter-mB interference, however when the beams are very narrow (as for the 9 beams case), the results are sensitive to the tilt angle. This is seen where the performance for the 7 beams/array scenario outperforms the 9 beams/array case. For the 9 beams/array case, the 0◦ tilt angle is superior to the −15◦ tilt angle but there are cases in which having a down-tilt is helpful such as when the UE is very close to the mB, shown in figures 3 and 4 as (T). This is seen by noting the significant improvement when the best of the two tilt angles is chosen for each UE, the 18 beams/array in figures 3 and 4. B. Interference Interference is a matter of concern in all wireless systems. To determine the effect of interference, we calculate a hypo- thetical value which is the SNR throughput. The SNR through- put is the achieved throughput assuming zero interference. Comparing this value to the achieved SINR throughput, one can determine the effect of the interference on the system under study. Figure 5 shows the SNR and SINR UE throughput CDF. The mBs in this test are assumed to have 5 beams/array. Two schedulers have been tested, the Round Robin and the proportional fair schedule (PF) [9] schedulers. A PF is considered to balance between delay and fairness constraints and maximizing the network throughput. The results show that 0 500 1000 1500 2000 2500 3000 3500 0 10 20 30 40 50 60 70 80 90 100 User Throughput (Mbps) CD F (% ) 5 beams/array−5mB 7 beams/array−4mB 9 beams/array−4mB 5 beams/array−5mBs 7 beams/array−5mBs 9 beams/array−5mBs 9 beams/array−5mBs (T) 18 beams/array−5mBs Fig. 3: User throughput for various mBs deployments 0 10 20 30 40 50 60 70 80 0 10 20 30 40 50 60 70 80 90 100 Total Cell Throughput (Gbps) CD F (% ) 5 beams/array−5mB 7 beams/array−4mB 9 beams/array−4mB 5 beams/array−5mBs 7 beams/array−5mBs 9 beams/array−5mBs 9 beams/array−5mBs (T) 18 beams/array−5mBs Fig. 4: Total cell throughput for various mBs deployments even for the Round Robin scheduler, the SNR throughput and the SINR throughput are very close to each other. This is because of the mmW characteristics (high path loss, material absorption, limited diffraction and the Oxygen absorption) in addition to the use of the transmitter narrow beams. This result shows that a mmW system is not an interference limited system and pushing more power in the system will increase system capacity. C. Modulation We consider various upper limits on modulation schemes when mapping SINR to throughput. QPSK, 16-QAM and 64-QAM tables based on LTE from [7] are used to map the calculated SINR to the achieved throughput. We compare these results with the Shannon capacity SINR to throughput mapping. Modulation and coding schemes based on IEEE 802.11ad [8] are tested as well, one is based on single carrier (MCS indices 1-12) and the other is based on OFDM (MCS indices 13-24). Figure 6 shows the total cell throughput CDF. Because of the availability of bandwidth, a simple modulation scheme can be used where this would be enough to provide a high quality4148 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 0 10 20 30 40 50 60 70 80 90 100 User Throughput (Mbps) CD F (% ) SINR throughput−RR SNR throughput−RR SINR throughput−PF, B=1 SNR throughput−PF, B=1 Fig. 5: SINR throughput vs SNR throughput 0 10 20 30 40 50 60 70 80 90 0 10 20 30 40 50 60 70 80 90 100 Total Cell Throughput (Gbps) CD F (% ) SC−802.11ad MCS OFDM−802.11ad MCS Shannon Capacity QPSK 16−QAM 64−QAM Fig. 6: Total cell throughput for various modulation schemes of service and at the same time reduces receiver complexity. This can be shown from the results in the figure where even when limiting the modulation scheme to QPSK, the mmW system provide performance that exceed any known deployed technology. The average total network throughput for QPSK is 29.8 Gbps. The area of the college campus is 0.076 km2 and with that average network throughput, a throughput of 392 Gbps/km2 can be achieved. D. Receive Antenna Pattern Both one- and two-sided uniform rectanguar and uniform linear beam directional antennas are used at the receiver. Based on the total received power, the receiver selects the beam pattern that maximizes the total received power. We compare 5 antennas at the UEs: 1) a 0 dB uniform gain ideal omni- directional antenna 2) a planar phased array that can generate 5x1 beams (azimuth steering only), 3) a planar array antenna that can generate 5x3 beams (azimuth and elevation steering), 4) two back-to-back planar phased array antennas each can generate 5x1 beams (azimuth steering only), and 5) two back- to-back planar phased array antennas each can generate 5x3 beams (azimuth and elevation steering). 0 500 1000 1500 2000 2500 3000 3500 0 10 20 30 40 50 60 70 80 90 100 User Throughput (Mbps) CD F (% ) Ideal omni dir planar array 5x1 dir planar array 5x3 2 dir planar array 5x1 2 dir planar array 5x3 Fig. 7: User throughput under various Rx antennas 0 5 10 15 20 25 30 35 40 45 0 10 20 30 40 50 60 70 80 90 100 Total Cell Throughput (Gbps) CD F (% ) Ideal omni dir planar array 5x1 dir planar array 5x3 2 dir planar array 5x1 2 dir planar array 5x3 Fig. 8: Total cell throughput under various Rx antennas Figures 7 and 8 show the user throughput and the total cell throughput, respectively. A general observation is that the use of directional antennas can benefit the system compared to an ideal omni antenna. An omni directional antenna outperforms the 5x1 beam antenna since the range that this directional antenna covers is limited compared to the omni-directional antenna. Adding the two back-to-back antennas was beneficial where this expands the azimuth angle over which the UE can receive signal to almost 360◦. The down-tilted and the up- tilted beams are very important because of the directivity of the receive beam patterns and allows the possibility of the UE to be oriented in any direction. This effect should be clearer with higher modulation schemes where the extra gain provided by the antenna in case of QPSK might not be used due to its limited spectral efficiency. E. mmW System Threshold A threshold for the average UE total received power is used to determine whether the UE should be served with mmW service or not. This guarantees a high throughput and a good use of of the mmW resources. The UEs that are not served with mmW are still covered by the cellular underlay.4149 0 500 1000 1500 2000 2500 3000 3500 0 10 20 30 40 50 60 70 80 90 100 User Throughput (Mbps) CD F (% ) mmw RX thr =−Inf mmw RX thr =−90 mmw RX thr =−85 mmw RX thr =−80 mmw RX thr =−75 mmw RX thr =−70 Fig. 9: mmW UE throughput CDF −Inf −90 −85 −80 −75 −70 0 10 20 30 40 50 60 70 80 90 100 mmw RX power service threshold Pe rc en ta ge o f U Es s er ve d wi th m m w Fig. 10: mmW penetration percentage We test various received power thresholds by calculating the percentage of mmW penetration and the performance of the total system in terms of throughput. Figure 9 shows the mmW UE throughput CDF and Figure 10 shows the percentage of UEs that are served with mmW with respect to all UEs in the system. Note that there is a trade-off between the mmW penetration percentage and throughput. Using a high threshold guarantees a high service quality but at the same time will limit the number of UEs that are served. In the system under study, -80 dBm is considered a good threshold that guarantees 90% mmW penetration and around 200 Mbps tenth percentile UE throughput. IV. URBAN DEPLOYMENT Identical metrics have been generated for a small urban morphology which is loosely based on a portion of London, England in which a series of uniform buildings of similar dimensions are laid out in a uniform pattern. This deployment includes a high preponderance of urban canyons. Figure 11a shows a 2-D view of this scenario for 7 mBs and 16 arrays while Figure 11b shows the identical scenario with 9 mBs and 25 arrays. In both cases, adequate SNR coverage can be provided down the urban canyons but the denser deployment provides increased network throughput due to higher signal strength overcoming the effects of additional interference. (a) 7 mBs/16 arrays (b) 9 mBs/25 arrays Fig. 11: Urban deployment Fig. 12: User throughput, Urban Scenario Figures 12 and 13 show the user and total throughput CDF. The main result is that adding more mBs and antenna arrays provides significant performance improvement. The median total cell throughput was improved by over 40% by increasing the number of mBs from 7 to 9. A. Inter-site Distance A single street (urban canyon) was created with mBs posi- tioned at either end 600m apart. mBs use 20x20 URA antenna arrays. Additional mBs are then equally spaced between the end points to determine the performance gains for a higher base station density and to determine if there becomes a point of diminishing returns in which further reducing inter-site distance (ISD) provides little benefit. The median total throughput was plotted for a varying number of mBs, Figure 14a. Continuing to add mBs improves performance as the received signal power increases with the reduced mB-UE distance. In Figure 14b the median UE throughput is plotted for the cases in which the throughput is mapped to the SINR as well as to the SNR. The latter is a purely hypothetical exercise designed to estimate the impact of interference on user throughput. Without interfer- ence, the throughput improves linearly with the increasing mBs (decreasing ISD) and when interference is considered, the throughput improvement begins to level off. Taken together,4150 Fig. 13: Total cell throughput, Urban Scenario 2 3 4 5 6 7 0 2 4 6 8 10 12 14 16 18 20 Number of mBs Th ro ug hp ut (G bp s) (a) Median network throughput 2 3 4 5 6 7 0 100 200 300 400 500 600 Number of mBs Th ro ug hp ut (M bp s) SINR SNR (b) Median UE throughput Fig. 14: Single street the results show that an ISD of 150 m yields good performance but further reducing ISD provides diminishing returns. B. Effects of mB Placement An outdoor shopping plaza was created to accommodate 32 potential storefronts, Figure 15a. Obviously not every store will supply enhanced WiFi service but some will as shown by the red dots. As a result, the number of storefronts providing mmW service was treated as a simulation variable where the locations supplying mmW service are then randomly selected. For several combinations of active mBs, numerous random mB â ˘AIJdropsâ ˘A˙I are done to determine system wide performance sensitivity to the positioning of the mBs. Figure 15b shows the total throughput CDFs for 4 (blue), 8 (green), and 16 (red) active mBs. It is clear that network performance improves when more mBs are active; however, the absolute spread between the best and worst drops increases with the number of active mBs. The median throughput improves significantly with the number of active mBs while the relative spread â ˘AS¸ measured as the ratio of the median throughputâ ˘A ´Zs standard deviation to its mean â ˘AS¸ is largest with only 4 active mBs. This means that there is greater sen- sitivity to mB placement when there are few mBs. In general, performance improves with the increasing number of mBs so it is reasonable that uncoordinated mmW deployments are viable though performance would be better if the active mBs were chosen with some coordination (e.g. 22% improvement (a) A random plaza deployment (b) mB drops total throughput Fig. 15: mB placement sensitivity between the min and max cases for 16 mBs). V. CONCLUSION A system level simulation for a network of a small mmW base stations that are overlaid on a cellular network is carried out for a university campus and an urban area. Results show that a goal of around 400 Gbps/km2 total network throughput can be easily achieved even with simple modulation and coding schemes. The characteristic of the 60 GHz carrier frequency and the use of transmit antennas with narrower beamwidths result in less inter-mB interference and, therefore, better overall performance. It is shown that placing mBs 150 m apart is adequate as long as there are clear lines of sight between possible UE locations and nearby mBs. Double sided directional receive antennas are necessary to at least provide the same performance as that of an ideal omni. Uncoordinated placement of mBs can be supported since adding mBs always improves overall performance and the increase in intercell interference is more than offset by the reduced UE-mB distance. REFERENCES [1] W. Jing, R. Prasad, and I. Niemegeers, “Analyzing 60 GHz radio links for indoor communications,” IEEE Transactions on Consumer Electronics, vol. 55, no. 4, pp. 1832–1840, Nov. 2009. [2] J. Wang, R. Prasad, P. Pawelczak, and I. Niemegeers, “A link stability model for indoor 60GHz radio wireless networks,” in Vehicular Technol- ogy Conference Fall (VTC 2009-Fall), 2009 IEEE 70th, sept. 2009, pp. 1 –6. [3] H. Lee, J. Bok, B. G. Jo, G. H. Baek, and H. G. Ryu, “Indoor WPAN communication system using 2-dimensional array antenna in 60GHz frequency band,” in Computing, Communications and Applications Con- ference (ComComAp), 2012, jan. 2012, pp. 158 –161. [4] X. Zhang, L. Lu, R. Funada, C. S. Sum, and H. Harada, “Physical layer design and performance analysis on multi-gbps millimeter-wave wlan system,” in Communication Systems (ICCS), 2010 IEEE International Conference on, nov. 2010, pp. 92 –96. [5] Z. Pi and F. Khan, “System design and network architecture for a millimeter-wave mobile broadband (mmb) system,” in Sarnoff Sympo- sium, 2011 34th IEEE, may 2011, pp. 1 –6. [6] AWE Communications, “WinProp software suite,” http://www.awe- communications.com. [7] “IEEE 802.16m evaluation methodology document (EMD),” IEEE 802.16 Broadband Wireless Access Working Group, Jan 2009. [8] “IEEEdraft standard for local and metropolitan area networks-specific requirements-part 11: Wireless LAN medium access control (MAC) and physical layer (PHY) specifications. amendment 3: Enhancements for very high throughput in the 60 GHz band,” IEEE802.11ad, Mar 2012. [9] D. Tse and P. Viswanath, Fundamentals of Wireless Communication. Cambridge University Press, 2005.4151