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# Communication Systems Simulation - I Harri Saarnisaari

Communication Systems Simulation - I Harri Saarnisaari Part of Simulations and Tools for Telecommunication Course. Introduction. First we study what simulation methods are available Then we study the structure of communication systems and discuss their simulations. Simulation methods.

## Communication Systems Simulation - I Harri Saarnisaari

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1. Communication Systems Simulation - I Harri Saarnisaari Part ofSimulations and Tools for Telecommunication Course

2. Introduction • First we study what simulation methods are available • Then we study the structure of communication systems and discuss their simulations

3. Simulation methods • Monte Carlo (MC) method • Repeated random trials • Quasianalytical (QA) method (or semianalytical) • Average signal (e.g., bit/symbol decisions) is obtained by passing a noiseless signal through the system • Simulation part of QA • Average is then used to obtain the result via analytical tools • Assumed noise statistics is used • Analytical part of QA • May be also mixed with the MC method • Also other less used techniques exits • Only the MC method will be discussed

4. Monte Carlo method • Since the communication signals are random, a single realization does not explain the whole story • It may even yield to misleading conclusions • E.g., you send (in a simulator) a bit through a bad channel and receive it correctly and then claim that BER is 0 although it really is 0.4 after serious simulations • Several realizations are needed to see the average behavior • convergence to the average value: consistency • In the MC method the same experimental is repeated several times such that random phenomena in the process are modeled as random variables and generated again and again using random number generators (RNGs)

5. How many trials are needed? In order that statistical measures are reliable, a certain amount of experiments have to be made The larger the number of trials N is, the reliable the results are since Average often converges to the actual value Confidence intervals tend to zero at rate (1/N)1/2 i.e., as N increases The average of trials becomes closer the actual value Interval at which the actual value is within certain limits of the average becomes smaller Monte Carlo methods

6. Monte Carlo methods

7. Monte Carlo methods • BER analysis • The theory of sequence of Bernoulli trials (which MC method essentially is) says that • 10-100 successful experiments (i.e., bit errors) have to be made in order that BER analyses are reliable • This means that for BER 10-5 we have to send at least 106 bits or 107 bits for more reliable results, both very large numbers • At very low BER simulation time may become very long • Usually simulations are stopped somewhere BER > 10-5 • Simulations may be arranged such that you have a maximum number of iterations Nmax and a minimum number of errors Nerr • Simulation is stopped whichever limit is first reached • This fastens simulations at low SNR/SINR since Nerr is usually achieved much faster than Nmax

8. Monte Carlo methods • Estimation algorithms are needed, e.g., in channel estimation and synchronization • In estimation algorithm studies simulations concern • the mean and variance of the estimator and/or • the probability that the estimator finds and/or does not find the correct value • For the latter case previous BER rules can be used, i.e., 10-100 successful measurements • For the former the used minimum number of trials is usually 100 although 1000 is better

9. General • A communication system designer has requirements the system has to satisfy and also limitations that has to be taken in the account • Simulations (in addition to analysis and prototyping) are used to verify are requirements and limitations possible to satisfy

10. Some possible requirements • Bit error rates the system has to support • May be different for different services • voice, data, video,… • BER targets • May be different for different services: • voice, data, video,… • Number of users • Users should be networked possibly in different ways • Level and type of interference the system has to tolerate • Interference from other systems at nearby frequency bands • Intentional interference in military systems • The system possibly has to operate in different environments • The system has to have connections to other systems • …

11. Some possible limitations • Costs • Size of equipments • Power consumption • Interference to other systems • …

12. General • Communication systems can be considered at different levels • higher and lower levels contain different parts of the systems • Communication nodes jointly form (communication) networks (higher level) • Different (kind of) networks jointly form larger networks • Nodes are connected through (communication) links (lower level) • Links consists of • Transmitter • Propagation medium (optic, wired, wireless) • Receiver • At different levels the simulations concern different things

13. Networks are usually linked somehow since the goal in communications is to send information from a place to another (not just inside a network) Networks and links are just means to attain the goal

14. Network level simulations • Throughput as a function of the number of nodes or some other variable • Latency (delay) and jitter (change of delay) of messages • Usability and effects of • Routing protocols, • Access protocols (like Carrier Sensing), • Packet addressing protocols (like IPv6), • QoS (quality of service) protocols (like packet priority) • Scalability of protocols • Does them work with different number of nodes? • …

15. Network level simulations • One has to think what are relevant features the network simulator has to have • Usually links are modeled using a high level model • Link budget is calculated for the desired and interfering signals • Gives SINR (signal-to-interference-plus-noise ratio) • BER is calculated analytically based on SINR, • i.e., transceivers are not actually simulated • This saves efforts, time and costs • This is QA method

16. Network level simulations • Random features in network simulations may be • Packet length • Packet arrival times • Packet arrival rate • Number of active users • Number of connections • Length of connections

17. Link level simulations • Obtained BER at different channels using different modulations and receiver algorithms • Supported bit rates at different channels (BER goals in mind) • RF and antenna design • Effects of uncertainties in synchronization/channel estimation to BER • Performance of different synchronization and channel estimators (algorithms) in different environments • … • We consider the link level hereafter (since the book does it too)

18. Link simulations • Random elements are • Data symbols (bits) • Additive (thermal) noise • Amplitude and phase of multipath components (in fading channels) • Number of multipath components • Frequency error in some channels • Delay (time-of-arrival) • Direction-of-arrival (in multiantenna channels) • …

19. Typical elements of a link To RF frequency, power amplification Digital signal formation Effects of RF/DA Coding part Radio channel Other signals channel estimation Effects of RF/AD Thermal noise From RF to IF/baseband Digital signal processing for demodulation/synchronization/ channel estimation Decoding part

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