Recent Results in Wireless Systems: From Smart Roaming to the Use of Wide Channels in 802.11ac Catherine Rosenberg Canada Research Chair in the Future Internet CISCO Research Chair in 5G Systems This work was done in collaboration with B. Venkitesh, S. Malekmohammadi, R. Stanica 1
Outline • WiFi Networks: Channel Allocation in WiFi.ac • Cellular Networks: Smart Roaming 2
WiFi ac IEEE 802.11 ac (WiFi 5) Features and Parametrization • Features : • Channel bonding (20/40/80/160 MHz) • Using more MIMO spatial streams (8) • Using denser modulation schemes (256 QAM) IEEE 802.11 ac channel allocation in the 5 GHz band • The allocation of the resource and the parametrization are critical, especially in dense environments, to provide good performance: • Channel (size and id) • Transmission power of each AP • Carrier sensing threshold (CST) used by each AP • Research questions : When is it better to use wider channels? When is it better to use lower power? 3
WiFi ac Current Practice in Industry Power: 2 main trends Fixing the transmission power for each AP to a high fixed value (usually the maximum power defined in the standard) Assigning dynamic power values to APs obtained from a power management algorithm. These values are always greater than a lower bound P TPC that we compute. CST: Usually, a default value is used (e.g. -82 dBm). Channel and Bandwidth: Having fixed the other two parameters, there are different ways to allocate channels, the general trend being to allocate narrower channels as the network density increases. Most of the works in the literature study the effect of only one of the channel bandwidth, transmission power and CST parameters on the networks performance, while the other two are fixed. There are also some proposed algorithms for power management and channel allocation, but the two are performed independently from each other by a central controller. 4
WiFi ac Our Claim There is need to study the impact of the three parameters together . Much gain can be obtained by using wide channels with low power (instead of using narrow channels with high power) 5
WiFi ac Benchmarks Benchmark 1 : use maximum power, default CST and select smaller size channels when the network is dense (By the way when is a network deemed dense is not typically defined). Benchmark 2 : a solution proposed by CISCO that allocates power and channel dynamically but with a power that is always greater than a value that we computed. 6
WiFi ac Framework We use NS3 to simulate realistic WiFi networks of different densities. We only consider downlink transmissions, as this is the main use case in WiFi networks. To simplify the search space and to have only one 160 MHz channel, we only consider one band of 160 MHz. We also use the same channel width, power and CST for all APs (except when otherwise noted). Topology : we consider an enterprise WiFi network with 64 identical APs located on four floors of a building. In each room, there is one AP associated with four users. L L 7
WiFi ac Framework Channel Propagation and Power: We use the NS3 Log Distance Propagation Loss Model. There is a maximum power of 23 dBm (200 mW). Consequently, when using a channel width of 20, 40, 80 and 160 MHz, the maximum power that can be used over each 20 MHz sub-channel (P 20 t ) is equal to 23, 20, 17 and 14 dBm, respectively . Coverage and Transmission Power: We define the coverage range of an AP as the closest distance at which a receiver is not able to decode the transmitted signal. We can compute it easily given P 20 t or alternatively we can find the minimum t,min = 30 Log 10 ((( L+5)/√2) + 5) - 47.33 power P 20 t,min for a given range R. For our topology: P 20 The lower L, the higher the deployment density and the lower the corresponding P 20 t,min Traffic and Overall Performance Metric: We assume a full buffer UDP traffic with a uniform arrival rate of 230 Mbps. The overall performance metric that we use is the geometric mean (GM) of the throughput of all the users: GM tot = N √ (∏ u λ u ) 8
WiFi ac Results Same channel width, power and CST for all APs. L= 40m (low density). The best performance is ≈ 84 Mbps, obtained for t ≈ 6 W = 160 MHz and P 20 dBm. P 20 Benchmark 1 Benchmark 2 Proposed Method t,min L= 40m, 35 Mbps 53 Mbps 84 Mbps 67.6 Mbps (W = 160 MHz) (W = 160 MHz) (W = 160 MHz) (W=160 MHz) (P 20 (P 20 (P 20 (P 20 t = 14 dBm) t = 11 dBm) t = 6 dBm) t = -0.347 dBm) 9
WiFi ac v Results v • Same channel width, power and CST for all APs. • L= 25m (medium density): P 20 Benchmark 1 Benchmark 2 Proposed Method t,min L= 25m, 11.87 Mbps 29.49 Mbps 53.52 Mbps 44.7 Mbps (W = 160 MHz) (W = 160 MHz) (W = 160 MHz) (W = 160 MHz) (P 20 (P 20 P 20 P 20 t = 14 dBm) t = 8 dBm) t = 0 dBm t = -4.77 dBm 10
WiFi ac Results v • Same channel width, v power and CST for all APs. • L= 15m (high density) v v P 20 Benchmark 1 Benchmark 2 Proposed Method t,min L= 15m, 5 Mbps 8.72 Mbps 25.98 Mbps 22.2 Mbps (W = 20 MHz) (W = 20 MHz) (W = 160 MHz) (W = 160 MHz) (P 20 (P 20 P 20 P 20 t = 23 dBm) t = 10 dBm) t = -5 dBm t = -8.87 dBm 11
WiFi ac Results • We have used so far the same channel width, power and CST for all Aps. • In that case, the best power value depends among other things on the density of the network. The denser the network, the lower the best power . • Using the largest channel width with lower power (even with P 20 t,min ) is significantly more effective than using a narrow channel width with any power. • However, in high density deployments, there is an unfairness among APs in the network, even when using the best power value! L=15m 12 L=25m
WiFi ac Results To alleviate this unfairness problem, we have tried to adjust the power and CST differently for poor APs: Increasing their CST so that they can get access to the shared channel more easily Increasing their transmission power values slightly (the other APs keep the power value determined earlier; i.e., for the case with equal parameters) so that they can combat the higher interference that they experience C poor + P poor + GM tot AM tot GM min none none 22.8 29.51 3.92 3 none 23.18 29.72 9.23 6 none 24.24 30.05 9.47 none 3 22.27 29.14 7.21 3 3 21.04 28.58 7.49 3 6 21.14 28.56 7.52 It is better to increase the CST of poor APs instead of increasing their power values 13
WiFi ac Results (GM in Mb/s) Benchmark 1 Benchmark 2 Proposed Method L= 15m, realization 0 5 8.72 25.98 L= 25m, realization 0 11.87 29.49 53.52 Performance (GM tot ) of the proposed and benchmark methods for random realizations of users and APs L= 40m, realization 0 35 53 84 L= 15m, realization 1 4.65 9.66 27.91 L= 25m, realization 1 12.96 26.47 52.52 L= 15m, realization 2 4.85 8.97 27.85 L= 25m, realization 2 13.67 25.03 52.71 14
WiFi ac Conclusion Densely deployed networks are characterized by many APs serving small coverage areas. So it is not necessary for the APs to use high values of power. Instead, allocate low values of power to them and use wide channels. 15
Outline • WiFi Networks: Channel Allocation in WiFi.ac • Cellular Networks: Smart Roaming 16
Smart Roaming Introduction • 5G is emerging to meet the ever increasing demand for mobile applications: • 4G on steroids + • Critical applications + • IoT 1000x Mobile Data Volumes 10x-100x Connected Devices 5G 4G 3G 2G 1G 5x Lower Latency 10x-100x End User Data Rates 10x Battery Life for Lower Power Devices [1] Qualcomm Technologies, Inc. , Leading the world to 5G, February 2016 17
Smart Roaming 5G in a nutshell • 5G wireless networks promise dramatic improvements in terms of data rate, spectral efficiency, user experience, mobility, latency, and connectivity over current state of the art 4G networks. • Achieving the promise of 5G will require a dramatic rethink of wireless networks. • Everyone is talking about the PHY technologies that will enable 5G, i.e., massive MIMO, mmwave, full duplex, etc. • However, 5G will also need advances at the higher layers, e.g., at the MAC and transport layers and old concepts need to be revisited: e.g., spectrum sharing and new concepts need to be adapted to wireless, e.g., slicing. 18
Smart Roaming Resource Management: The Focus of My Work We consider a multi-cell OFDMA system comprising several base-stations (BTS). Uplink Downlink The resources are: channels , power (on the downlink), time . The resource management processes are: Channel allocation to the BTSs; User association; User scheduling to allocate locally time, channel and power on a fast time scale. 19
Smart Roaming Our focus: coordination and cooperation (1) • Cellular networks consist of multiple base-stations, possibly heterogeneous. • The online operation of a BTS is affected by its neighboring BTSs because mainly of inter-cell interference (ICI). • Coordination between BTSs can provide significantly improved performance. This can be achieved through Cloud-RANs . • For example, user scheduling, resource allocation, beamforming, or mobility management (e.g., BTS handover) could benefit from BTS coordination at the cost of information exchange and possibly relocating some of these processes in the network. 20
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