Where’s that fu*#}ng Wi-Fi ?!? EFFICIENT Wi-Fi deployments The basics Just some common sense rules put together in a nice set of colorful slides Eduard Garcia-Villegas Dept. of Network Engineering eduardg@entel.upc.edu Contents EFFICIENT Wi-Fi deployments o Big vs. small o Analyze requirements o #STAs and #Needed radios o Available channels o Reuse factor o Dimensioning cells o Optimization by Podere Casanova Efficient Wi-Fi deployments 2 Wi-Fi deployments: intro In the era of ubiquitous Internet… Wireless internet access can be a traumatic experience due to o Many concurrent users (dense scenarios) o Coexistence (older/slower devices, other technologies sharing the band, etc.) o … o POOR DESIGN Efficient Wi-Fi deployments 3 Wi-Fi deployments: big vs. small (1) Coverage-driven design o In the past: maximize cell size && minimize costs • Optimize AP location and increase cell size less APs needed (lower cost) • Problems: – more devices per AP (lower per STA throughput) » Reduced efficiency due to higher collision probability 5 STAs x AP <2 STAs x AP VS. = AP = STA Efficient Wi-Fi deployments 4 Wi-Fi deployments: big vs. small (2) Coverage-driven design o In the past: maximize cell size && minimize costs • Optimize AP location and increase cell size less APs needed (lower cost) • Problems: – Longer distances AP STA mean worse signal quality and, hence, more robust (slower) PHY rates are used » Capacity of the whole cell is reduced » Longer tx time more power consumed and more collisions LAME! = AP = STA Efficient Wi-Fi deployments 5 Wi-Fi deployments: big vs. small (3) Coverage-driven design o In the past: maximize cell size && minimize costs • Optimize AP location and increase cell size less APs needed (lower cost) • Problems: – More hidden nodes more collisions – Power mismatch: AP (high tx power) and STA (low tx power) » STA can hear the AP, but the AP can't hear the STA » If you want a big cell, increase the antenna gain, not the tx power! HIDDEN NODES! CAN’T REACH ITS AP! = AP = STA Efficient Wi-Fi deployments 6 Wi-Fi deployments: big vs. small (4) Coverage-driven design o In the past: maximize cell size && minimize costs • Optimize AP location and increase cell size less APs needed (lower cost) • It has problems in present (dense) deployments. Other key aspects o KPI requirements o Client and AP capabilities • Are modern ≥ 11n capable (how many antennas)? Coexistence with 11a/b/g? Dual band? o Propagation phenomena • Outdoor/indoor? APs mounted on ceiling, walls or floor? o User density Efficient Wi-Fi deployments 7 ANALYZE REQUIREMENTS Per user #STAs per RADIO AVAILABLE CHANNELS Total #RADIOS NEEDED Efficient Wi-Fi deployments REUSE FACTOR DIMENSION CELLS The basics Analyze requirements OPTIMIZE/ TROUBLESHOOT Wi-Fi deployments: requirements The first thing is to identify key performance indicators (KPI) o Minimum bandwidth required to satisfy supported applications o Maximum latency tolerated o Expected Min-Avg-Max number of active devices Examples (per-user requirements): o School o Convention center (1500 att.) • BW: <3Mbps • BW: <1 Mbps • Delay tolerance: low • Delay tolerance: Medium • Users: “educated guess” (video streaming; desktop/file sharing) (video streaming; intranet login) • Users: Min-Avg-Max = up to 30 per classroom Efficient Wi-Fi deployments (web browsing; e-mail) – 70% will connect Wi-Fi device – 50% simultaneously – 1500 x 0.70 x 0.5 = 525 9 Wi-Fi deployments: #STAs and radios Capacity-driven design (rule of thumb) o Example 1 school (<3Mbps x 30 users per classroom): • 20 STAs per AP each classroom served by two radios (two APs or one dual band AP) – Assume homogeneous (IT-controlled) 11n 2x2 devices – Good signal quality (high rates available) STAs achieve ~80Mbps of net throughput (isolated) – Allow future growth: AP utilization ≤ 75% 75/(100*3Mbps/80Mbps) = 20 STAs per AP o Example 2 convention center (<1Mbps x 525 users) • 32 STAs per AP 525/32 = 16 – 17 radios – Assume heterogeneous (BYOD) devices – Diverse signal quality STAs achieve ~40Mbps of net throughput – AP utilization ≤ 80% 80/(100*1Mbps/40Mbps) = 32 STAs/AP Efficient Wi-Fi deployments: the basics 10 ANALYZE REQUIREMENTS Per user #STAs per RADIO AVAILABLE CHANNELS Total #RADIOS NEEDED Efficient Wi-Fi deployments REUSE FACTOR DIMENSION CELLS The basics Available channels OPTIMIZE/ TROUBLESHOOT Wi-Fi deployments: channels (1) Capacity limited by the scarcity of available spectrum o 2.4GHz ISM band • Only three non-overlapping channels (1,6,11) • Four (almost) non-overlapping channels (1,5,9,13) where available Ch1 Ch11 Ch1 Ch1 Ch11 Baseline capacity Ch5 Ch11 Ch6 Ch6 Three channel scheme: Baseline x3.05 Three channel scheme: Baseline x3 Efficient Wi-Fi deployments: the basics Ch13 Ch9 Four channel scheme: Baseline x3.9 12 Wi-Fi deployments: channels (2) Capacity limited by the scarcity of available spectrum o 2.4GHz ISM band • Only three non-overlapping channels (1,6,11) • Four (almost) non-overlapping channels (1,5,9,13) where available – Not available in all regulatory domains (e.g. North Americas) – Many devices default to Americas config. will see coverage gaps in the areas served by APs in Ch13. • Highly congested: coexistence with WPANs, cordless phones, baby monitors, microwave ovens… o 5GHz ISM band • 15-21 non overlapping channels in different sub bands • Highly variable from one regulatory domain to another – Some channels only for indoor use, others require DFS – Different tx power limits … Efficient Wi-Fi deployments: the basics 13 ANALYZE REQUIREMENTS Per user #STAs per RADIO AVAILABLE CHANNELS Total #RADIOS NEEDED Efficient Wi-Fi deployments REUSE FACTOR DIMENSION CELLS The basics Reuse Factor OPTIMIZE/ TROUBLESHOOT Wi-Fi deployments: reuse factor #Radios Needed Reuse Factor = Available Channels o If Reuse Factor ≤ 1 LUCKY YOU! o Otherwise, each channel is shared among Reuse Factor APs INTERFERENCE! • Minimize interference by. – Carefully dimensioning cells – Smart channel management Efficient Wi-Fi deployments: the basics 15 ANALYZE REQUIREMENTS Per user #STAs per RADIO AVAILABLE CHANNELS Total #RADIOS NEEDED Efficient Wi-Fi deployments REUSE FACTOR DIMENSION CELLS The basics Dimension the cell OPTIMIZE/ TROUBLESHOOT Wi-Fi deployments: dimension cells (1) What is the cell radius? o Max distance at which frames can be decoded • Pt is tx power VERY FAST – Decreases with MCS (to avoid distortion) • Sr is receiver sensitivity R1 – Increases with MCS – Rr reception range 𝑷𝒕 𝑷𝒓 ≈ 𝜶 ⟶ 𝑹𝒓 ≈ 𝒅 𝑷𝒕 𝑺𝒓 𝟏 R2 Rn 𝜶 SLOW – d is the distance tx rx – α is the path loss exponent o Different radius depending on targeted MCS Efficient Wi-Fi deployments: the basics 17 Wi-Fi deployments: dimension cells (2) How to set cell radius for Wi-Fi small cells? o Reduce AP’s tx power • Reduces interference over other cells • Avoids AP/STA power mismatch • Reduces suitable rates NOT SO FAST SLOW Efficient Wi-Fi deployments: the basics 18 Wi-Fi deployments: dimension cells (3) How to set cell radius for Wi-Fi small cells? o Reduce AP’s tx power • Reduces interference over other cells • Avoids AP/STA power mismatch • Reduces suitable rates NOT SO FAST o Increase min tx rate of the cell • Reduces performance anomaly and allows higher average rate OUT! – Avoid “sticky” STAs • Possible unsupported devices – Accept, at least, 802.11b@11Mbps? Efficient Wi-Fi deployments: the basics 19 Wi-Fi deployments: dimension cells (4) BUT…interference goes beyond the cell edge o Carrier Sense Range (Rc) • Max distance at which frame preamble can be detected and, hence, prevent concurrent transmissions in the same channel. – Only 3dB SNR is enough! (>200m outdoors) – Behavior improved in IEEE 802.11ax o Beyond Carrier Sense Range • Transmitted frames are just noise Efficient Wi-Fi deployments: the basics LEAVE ME ALONE! 20 Wi-Fi deployments: dimension cells (5) Coverage strategy for maximal densification o Reduce reuse distance • Low gain directional antennas Ch1 reduced reuse distance Ch1 Ch1 Ch1 120º vs. 60º • AP placement – Overhead: AP installed on the ceiling/lamp posts facing down reuse coverage – Side: AP installed on walls/pillars – Floor: under floor/under seat (stadiums or auditoriums) – Even consider mounting APs behind walls/obstacles and avoid LoS (enriches multipath diversity leveraged by MIMO) Efficient Wi-Fi deployments: the basics 21 ANALYZE REQUIREMENTS Per user #STAs per RADIO AVAILABLE CHANNELS Total #RADIOS NEEDED Efficient Wi-Fi deployments REUSE FACTOR DIMENSION CELLS The basics Finishing touches OPTIMIZE/ TROUBLESHOOT Wi-Fi deployments: channel plan (1) In your dreams Ch11 Ch6 Reality(t) Ch11 Ch6 Ch1 Ch11 Ch1 Ch11 Ch6 Ch1 Dynamic and unpredictable spectrum utilization o License-free bands! Intelligent channel assignments are required Efficient Wi-Fi deployments: the basics 23 Wi-Fi deployments: channel plan (2) Automatic and dynamic channel assignments aimed at reducing interference maximizing performance o APs gather information of the environment • Number of APs detected • Power received from neighboring APs • Portion of time the channel was reported busy/idle by CCA Ch. X is free! NO INTERFERENCE! Ch. X is free! Efficient Wi-Fi deployments: the basics 24 Wi-Fi deployments: channel plan (3) Automatic and dynamic channel assignments aimed at reducing interference maximizing performance o APs gather information of the environment • Number of APs detected • Power received from neighboring APs • Portion of time the channel was reported busy/idle by CCA o Ideally, client STAs too (and report via IEEE 802.11k) Ch. X is free! Ch. X is free! Efficient Wi-Fi deployments: the basics 25 Wi-Fi deployments: channel plan (4) Automatic and dynamic channel assignments aimed at reducing interference maximizing performance o APs (ideally, STAs too) gather information of the environment • Number of APs detected • Power received from neighboring APs • Portion of time the channel was reported busy/idle by CCA o Distributed approach (autonomous APs) • Each AP periodically (and asynchronously) scans the medium and chooses the least congested channel local optimum • Alternatively, APs collaborate (exchange information) to produce better decisions o Centralized approach (controller-based) • APs send periodic reports to a controller – Knowing the whole picture and having more resources (i.e. CPU, memory, etc.) controller runs a sophisticated optimization algorithm global optimum Efficient Wi-Fi deployments: the basics 26 Wi-Fi deployments: channel plan (5) Other considerations o Partially overlapping channels • Chaotic environments (many rogue/unmanaged APs in random channels): take the most of the spectrum by allowing the whole channel set (not only non-overlapping) o Channel bonding • 40MHz or 80MHz channels provide higher rates but require more free spectrum not recommended in dense scenarios o Single Channel Architecture (SCA), aka Channel Blanket • All APs use the same channel and the same (virtual) BSSID so that all STAs “see” one single AP – Seamless handover: controller decides AP delivering DL traffic – Larger collision domain (although DL is scheduled by controller) © by Extricom Efficient Wi-Fi deployments: the basics 27 Wi-Fi deployments: load balancing (1) Wi-Fi users are quasi-static and tend to concentrate in space & time hot spots o Clients (i.e. traffic) unevenly distributed among APs • Some APs (channels) congested and some others underutilized o Load Balancing techniques could increase ability to satisfy QoS requirements A B C D E F • Load Balancing techniques widely used in cellular networks • Take advantage of overlapping areas between neighboring cells – Clients can be served by several BSs – System decides the best BS for a client depending on BSs’ loads • Not directly applicable to Wi-Fi WLANs – Clients decide association and roaming, not the network Efficient Wi-Fi deployments: the basics 28 Wi-Fi deployments: load balancing (2) Load balancing with client-driven association in WLANs o Typically, client STAs decide best AP based on RSSI measurements (i.e. strongest Beacon or Probe Response Frame) • Uneven distribution of users uneven distribution of load o Some APs broadcast load information (BSS Load element) and some clients do care about it o Network-oriented client-driven load balancing • Band steering: encourage utilization of the 5GHz band – If AP or controller detect a STA sending Probe Requests in the two bands do not send responses through 2.4GHz radios, only through 5GHz • Disassociation/blacklisting – Network decides STA’s best AP the rest of APs ignore that STA requests (if already associated, current AP sends Disassociation frame) • Cell Breathing: adapt size of the cell – Congested APs reduce tx power of Beacons and Probe Responses underutilized APs do the opposite Efficient Wi-Fi deployments: the basics 29 Wi-Fi deployments: load balancing (3) Example of cell breathing o Reduce power of Beacons and Probe Responses • do not reduce power of data frames since this will reduce suitable rates and increase error rate Cell A Cell B 3 1 2 4 Efficient Wi-Fi deployments: the basics 30 Wi-Fi deployments: load balancing (3) Example of cell breathing o Reduce power of Beacons and Probe Responses • do not reduce power of data frames since this will reduce suitable rates and increase error rate Cell A Cell B 3 1 2 4 Efficient Wi-Fi deployments: the basics 31 Wi-Fi deployments: The End Don’t forget the wires! o Data/power wires to APs • If not…multihop or mesh-based wireless distribution system o Uplink pipe • Imagine all this headache for just a DSL WAN connection… Efficient Wi-Fi deployments: the basics 32 Some references (1) Load balancing o Garcia-Villegas, E.; Vidal, R.; Paradells, J. (2006, June). “Load Balancing in WLANs through IEEE 802.11k Mechanisms,” in 11th IEEE Symposium on Computers and Communications, ISCC 2006. o Garcia-Villegas, E.; Vidal, R.; Paradells, J. (2008, July). “Cooperative Load Balancing in IEEE 802.11 Networks with Cell Breathing,” in 13th IEEE Symposium on Computers and Communications, ISCC 2008. o Garcia-Villegas, E.; Ferrer, JL.; Lopez-Aguilera, E; Vidal, R.; Paradells, J. (2009). “Clientdriven load balancing through association control in IEEE 802.11 WLANs”. European Transactions on Telecommunications, ETT vol. 20, no. 5, pp. 494-507. John Wiley & Sons. Sensitivity control o Afaqui, MS.; Garcia-Villegas, E.; Lopez-Aguilera, E.; Smith, G.; Camps-Mur, D. (2015) “Evaluation of Dynamic Sensitivity Control Algorithm for IEEE 802.11ax,” IEEE Wireless Communications and Networking Conference, WCNC 2015, pp. 1072-1077 o Afaqui, MS.; Garcia-Villegas, E.; Lopez-Aguilera, E.; Camps-Mur, D. (2016) “Dynamic Sensitivity Control Algorithm leveraging adaptive RTS/CTS for IEEE 802.11ax,” in IEEE Wireless Communications and Networking Conference, WCNC 2016 o Afaqui, MS.; Garcia-Villegas, E.; Lopez-Aguilera, E.; Camps-Mur, D. (2016) “Dynamic Sensitivity Control of Access Points for IEEE 802.11ax”, in IEEE International Conference on Communications, ICC’16 Efficient Wi-Fi deployments: the basics 33 Some references (2) Channel management o Garcia-Villegas, E.; Vidal, R.; Paradells, J. (2009). “Frequency assignments in IEEE 802.11 WLANs with efficient spectrum sharing”. Wireless Communications and Mobile Computing, WCMC vol. 9, no. 8, pp. 1125-1140. John Wiley & Sons o Mengual, E.; Garcia-Villegas, E.; Vidal, R. (2013, September). “Channel management in a campus-wide WLAN with partially overlapping channels,” in The 24th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2013 o Deek, L.; Garcia-Villegas, E.; Belding, E.; Lee, S-J.; Almeroth, K. (2011, December). “The Impact of Channel Bonding on 802.11n Network Management,” in 7th International Conference on emerging Networking EXperiments and Technologies, CoNEXT’11 o Deek, L.; Garcia-Villegas, E.; Belding, E.; Lee, S-J.; Almeroth, K. (2014). “Intelligent Channel Bonding in 802.11n WLANs,” IEEE Transactions on Mobile Computing, vol. 13, no. 6, pp. 1242-1255 o Deek, L.; Garcia-Villegas, E.; Belding, E.; Lee, S-J.; Almeroth, K. (2013, June). “Joint Rate and Channel Width Adaptation for 802.11 MIMO Wireless Networks,” in IEEE Conf. on Sensing, Communication, and Networking, Secon’13, pp. 167-175 (Nominee for the Best Paper Award) o Deek, L.; Garcia-Villegas, E.; Belding, E.; Lee, S-J.; Almeroth, K. (2015). “A practical framework for 802.11 MIMO rate adaptation,” Computer Networks, vol. 83, pp. 332-348 Efficient Wi-Fi deployments: the basics 34 Course offered at: EETAC - UPC Master's degree in Applied Telecommunications and Engineering Management IoT & Ubiquitous IP