Mathematical Modelling: Its Role in Squeezing the Most out of 5G for the IoT
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1 Mathematical Modelling: Its Role in Squeezing the Most out of 5G for the IoT Attahiru Sule Alfa (Acknowledgements: Dr. AbuGhazaleh & Dr. Awoyemi) Attahiru Sule Alfa 5G Systems May 3 rd, / 33
2 Presentation Outline 1 Brief History: Radio Communication Systems 2 Brief History: Role of Mathematical Models for Communication Systems 3 The 5G 4 The IoT 5 5G, IoT and Resource Allocation 6 How Mathematical Modelling Would Play a Major Role 7 Conclusions and Way Forward Attahiru Sule Alfa 5G Systems May 3 rd, / 33
3 Radio Communication Systems: Brief History Published in UK s Punch Magazine on December 26 th Attahiru Sule Alfa 5G Systems May 3 rd, / 33
4 Radio Communication Systems: Brief History Visionary caricature of Karl Arnold in 1926 entitles Berlin - Wireless Telephony. Attahiru Sule Alfa 5G Systems May 3 rd, / 33
5 Radio Communication Systems: Brief History The SCR-536 Handie Talkie used in World War II. Attahiru Sule Alfa 5G Systems May 3 rd, / 33
6 Radio Communication Systems: Brief History 1949: Mobile Telephone Service (MTS) was the first commercial radio-telephone service developed by AT&T. It was an operator-assisted two-way communication service where calls were routed by a mobile operator. Users were equipped with mobile push-to-talk handsets that weighed around 80 pounds. The initial deployment of the service had only 3 channels available for all users within a coverage area. 1965: Improved MTS (IMTS) was deployed which included additional radio channels and introduced operator-unassisted customer dialing. Attahiru Sule Alfa 5G Systems May 3 rd, / 33
7 Cellular Communication Systems: Brief History 1G Systems: 1970 s to 1980 s; Voice, Analog, using FDMA 2G Systems: 1990 s; Voice, Digital, using TDMA and a some CDMA (GSM) 2.5G Systems: Extension of 2G Data Services, GPRS 50 Kbips, data rate 1Mbps, EVDO 3Mbps(never took off) 3G Systems: 2001, Voice, Data & video signals CDMA, 3.1 Mbps & 42 Mbps download 4G Systems: 2009; Enhanced 3G; LTE peak download 100Mbps, LTEA 1 Gbps Attahiru Sule Alfa 5G Systems May 3 rd, / 33
8 Cellular Communication Systems: Brief History The evolution from 1G to 4G mainly involved changes in the channel access methods, i.e. FDMA TDMA CDMA OFDMA. So, will 5G just involve a further enhancement to the current channel access methods? Attahiru Sule Alfa 5G Systems May 3 rd, / 33
9 Progression from 1G to 4G, expectations and achievement 1G: Just happy we could do it! 2G & 2.5G: We are able to do better! The demand increased 3G: We are really doing much better, why not use more! 4G: Great, we can do very much better and handle most of the demand, now let s get users to want more Let s increase how much we can handle, as it appears that as we expand the network capacity it is fully consumed by users! How far is it going to go? Attahiru Sule Alfa 5G Systems May 3 rd, / 33
10 Mathematical Models Lag Behind Development of Technologies Growth of of technology Mathematical models lag behind technology growth despite the significant growth in mathematical modelling literature The two main areas of mathematical modelling of interest are; Optimization and Queueing models Attahiru Sule Alfa 5G Systems May 3 rd, / 33
11 Some Mathematical Models Used for Analysis and Design of the 1G to 2G For channel allocation, loss, etc; Erlang B and Erlang C models used Erlang models were developed in 1917 for PSTN connections Developed for circuit switched and later used for packet swicthed Erlang B model is the M/M/m/m model with P b = B(E, M) = E m m! [ m i=0 E i i! ] 1, where P b = blocking prob., m is the number of parallel (telephone lines) channels and E = λh, λ is arrival rate and h is av. service time These models are not appropriate for wireless systems Channel holding times no longer necessarily follow the Exponential distribution Poisson arrivals were most likely not appropriate in most cases A lot of research efforts were later devoted to finding more appropriate arrival processes, services processes and queueing models Attahiru Sule Alfa 5G Systems May 3 rd, / 33
12 Some Mathematical Models Used for Analysis and Design of the 3G and 4G With 3G, driven by CDMA (even though CDMA was adopted in 2.5G also), the mathematical modelling efforts focussed more on resource allocation This led to more work on optimization maximizing capacity, while allocating power and ensuring QoS is met Most of the optimization problems were non-convex and most results were based on heuristics, some for which how tight a bound they provided were not explored For 4G, driven by OFDMA, mathematical modelling efforts were on optimization and game theory Attahiru Sule Alfa 5G Systems May 3 rd, / 33
13 State of the Art in Mathematical Modelling for Wireless Communications Queueing system appear in different forms in modern day communication systems, including CRN, WSN, etc which are very unconventional We need more appropriate queueing models in order to design the systems better Similarly complex optimization problems for resource allocations occur in modern day communication systems, The optimization problems are usually just manageable using heuristics, however we need good (tight) bounds for them With 5G coming up soon, we cannot overlook the need for appropriate mathematical models. Attahiru Sule Alfa 5G Systems May 3 rd, / 33
14 The Visions for 5G Growth in 2016 Some facts from the Cisco VNI (February 2017 White Paper): Mobile data traffic has grown 18-fold over the past 5 years. Almost 1/2 billion mobile devices and connections were added in Average smartphone usage grew 38 percent in Attahiru Sule Alfa 5G Systems May 3 rd, / 33
15 The Visions for 5G - Forecasted Future Traffic Growth Some forecasts from the Cisco VNI (February 2017 White Paper): Mobile data traffic will grow at a compound annual growth rate (CAGR) of 47 percent from 2016 to 2021, By 2021, mobile-connected tablets and PCs will generate 8.0 GB of traffic per month, The Middle East and Africa will have the strongest mobile data traffic growth of any region with a 65 percent CAGR. Attahiru Sule Alfa 5G Systems May 3 rd, / 33
16 The Visions for 5G - Forecasted Future Growth in Number of Devices Some forecasts from the Cisco VNI (February 2017 White Paper): There will be 11.6 billion mobile-connected devices by 2021, Much of these M2M devices will consist of wireless sensors. Attahiru Sule Alfa 5G Systems May 3 rd, / 33
17 The Visions for 5G The forecasts suggest the need to have 5G network in place by 2020 Keep in mind induced traffic Would an evolution of the current channel access methods be sufficient to sustain this forecasted growth? Efficient and Effective management tools are needed -Hence Better Mathematical Models Attahiru Sule Alfa 5G Systems May 3 rd, / 33
18 The Visions for 5G Future 5G systems are expected to provide: increased throughput, lower latencies, lower outage probabilities and better coverage, high data rates, higher versatility and scalability, with lower infrastructure deployment costs. Attahiru Sule Alfa 5G Systems May 3 rd, / 33
19 What is IoT? A network of physical objects (devices, vehicles, equipment, homes, buildings, etc) The objects are connected to the internet through embedded devices and software, The connection allows these physical objects to collect, analyze and exchange data, and also control some activities. It is essentially an intersection of: people (making use of user-generated content), systems and things (that sense, communicate, network and produce new information) physical world (Real-world agents, autonomously expressing their capabilities and needs, and getting those needs met, to the benefit of us all) Attahiru Sule Alfa 5G Systems May 3 rd, / 33
20 Examples of IoT [Source: Wikipedia] Attahiru Sule Alfa 5G Systems May 3 rd, / 33
21 Abridged History of IoT After 1993 and before : Trojan Room Coffee (monitoring coffee level in the pot) Univ. of Cambridge 1994: Steve Mann creates WearCam 1997: Paul Saffo s article: Sensors: the next wave of infotech innovation 1998: InTouch developed at MIT by Professor Ishii and his team; Mark Weiser s exploration of water fountain s height mimicking volume and price trend of the stock market 1999: IoT term was coined by Kevin Ashton the final recognition of something new happening 2000: The Internet fridge 2002: The Ambient Orb 2005: ITU published its 1st report about IoT The rest is History Attahiru Sule Alfa 5G Systems May 3 rd, / 33
22 IoT in Tracking Technology: Gartner s Hype Cycle [Source: Gartner 2015] Attahiru Sule Alfa 5G Systems May 3 rd, / 33
23 Essentials of IoT Placement of devices and efficient data collection (via WSN) Security Low latency for data transmission Attahiru Sule Alfa 5G Systems May 3 rd, / 33
24 5G and IoT Source: Falahi and Alani (2017) Architectural Depiction of 5G and IoT internet MW Macrocell Femtocell & Wi-Fi (indoor solution) Mobile core network MM-wave small cell Dense small cell deployment Massive MIMO base station with beamforming In-field devices Sensors Weather devices Smart meters Sensors Massive M2M traffic due to billions of connected machines (Signaling + data) D2D Communication Massive MIMO/ beamforming Description of the interplay between 5G and IoT. Includes macrocells, microcells, femtocells, Wi-Fi, massive MIMO with beamforming, device-to-device (D2D) and machine-to-machine (M2M). Reference [1] Attahiru Sule Alfa 5G Systems May 3 rd, / 33
25 RA Problems & Solutions IoT The RA challenge for 5G and IoT is to develop models that can provide adequate resources for heterogeneous devices Solution goal is to provide an optimal mapping of multiple applications over 5G and IoT resources across different platforms Approaches Self-optimization Central optimization: involving classical tools such as LP, MILP, etc Multi-objective optimization Enhanced heuristics and meta-heuristics Attahiru Sule Alfa 5G Systems May 3 rd, / 33
26 How Mathematical Model Can Help With RA Issues The RA problem is driven by optimization There is a need to develop more efficient algorithms that have better bounds (tight bounds) to ensure most is SQUEEZED out of the available resources In order to squeeze the most out of the new 5G very good optimization tools are needed Attahiru Sule Alfa 5G Systems May 3 rd, / 33
27 How Mathematical Model Can Help With Latency Reduction? Given a very good RA solution, we still need to have queueing models for estimating latency Using Poisson models for arrivals or Exponential distribution for service is oversimplifying systems these days Most arrival processes are general and have some elements of correlation With M2M and D2D data arrivals are in platoon forms and more representative models are necessary Attahiru Sule Alfa 5G Systems May 3 rd, / 33
28 Geo/Geo/1 vs. MAP/Geo/1 Consider the example of a system where the arrival process is modelled as a MAP and system analyzed as a MAP/Geo/1 queueing system. Consider modeling the same system but instead assuming the arrival process to be Geometric with the same mean rate as the MAP. Mean Delay Geo/Geo/1 MAP/Geo/ Mean Arrival Rate Attahiru Sule Alfa 5G Systems May 3 rd, / 33
29 Geo/Geo/1 vs. MAP/PH/1 Consider the example of a system where the service process is modelled as a Phase-type process and analyzed as a MAP/PH/1 queueing system. Consider modeling the same system but instead assuming the arrival and service process to be Geometric with the same mean rate as the MAP and Phase-type process. Mean Delay Geo/Geo/1 MAP/PH/ Mean Service Rate Attahiru Sule Alfa 5G Systems May 3 rd, / 33
30 Issues that need attention in IoT Available capacity for data collection transmission (Resource Allocation) optimization Given reasonable resources managing them well to have low latency for transmission (Queueing models) Attahiru Sule Alfa 5G Systems May 3 rd, / 33
31 How can mathematical modelling help us? More accurate resource allocation models More accurate queueing models Attahiru Sule Alfa 5G Systems May 3 rd, / 33
32 How can mathematical modelling help us? Example with CRN More accurate queueing models PU uses channel 20 secs in every 60 secs to realize the full use of 40 secs by SU requires model that captures stochastic processes governing the distribution of the white spaces a stochastic model that properly captures the system behaviour is essential More accurate resource allocation models The remaining 40 secs have to be properly allocated to all the SUs allocations of 10:30 or 15:25 for two SUs, for example lead to different performance Attahiru Sule Alfa 5G Systems May 3 rd, / 33
33 Conclusions and Way Forward More accurate resource allocation models: Heuristics that have tighter bounds Good solutions should not be good enough; we need the best or at least very good solutions More accurate queueing models: Approximate queueing models that estimate delay more accurately are definitely preferred Claim that Poisson models give us an idea is not good enough. We need better estimation All these are needed in order to SQUEEZE the most out of 5G Attahiru Sule Alfa 5G Systems May 3 rd, / 33
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