Innovative Telecommunications Training through Flexible

IEEE COMMUNICATIONS MAGAZINE 1

Innovative Telecommunications Trainingthrough Flexible Radio Platforms

Ali Fatih Demir, Student Member, IEEE, Berker Peköz, Student Member, IEEE,Selçuk Köse, Member, IEEE, Hüseyin Arslan, Fellow, IEEE

Abstract—The ever-changing telecommunication industry is insevere need of a highly-skilled workforce to shape and deploy fu-ture generation communication systems. This article presents aninnovative telecommunication training that is designed to satisfythis need. The training focuses on hardware layers of the opensystems interconnection model. It integrates theory, numericalmodeling, and hardware implementation to ensure a completeand long-lasting understanding. The key telecommunication con-cepts that are covered in the fundamental training phase aredetailed along with best teaching practices. In addition, the meth-ods that enrich the learning experience, such as gamified micro-tasks and interactive use of daily telecommunication devices, arefeatured. The project development case studies that cultivatecreative thinking and scientific interest are highlighted. Also, awell-established guideline to compose the teaching environmentthat emphasizes hands-on experience is provided. Therefore, thepresented training can be exemplary to other institutions thatshare the same mission to educate the distinguished engineers ofthe future.

Index Terms—Engineering education, hands-on experience,interactive learning, teaching environment.

I. INTRODUCTION

TELECOMMUNICATION technologies have been evolv-ing from smoke signals to deep space high-definition

video conferences at an accelerating pace [1], [2]. Such athriving technology requires a vast number of highly skilledengineers. Therefore, a well-designed training is needed tosatisfy the ever-changing telecommunication industry’s thirstfor resilient professionals. Distinguished telecommunicationengineers must have a solid understanding of the fundamentaltheory, an ability to translate this theoretical knowledge tothe numerical implementation, and capability of implement-ing them in hardware. Also, they must be equipped withindependent thinking and creative problem-solving skills topioneer future telecommunication systems. Furthermore, theseprodigious engineers have to express their ideas clearly andfunction effectively on a team.

Manuscript received April 15, 2019; revised August 06, 2019; acceptedSeptember 02, 2019.

Ali Fatih Demir and Berker Peköz are with the Department of ElectricalEngineering, University of South Florida, Tampa, FL 33620 USA (e-mail:[email protected], [email protected]).

Selçuk Köse is with the Department of Electrical and Computer En-gineering, University of Rochester, Rochester, NY 14627 USA (e-mail:[email protected]).

Hüseyin Arslan is with the Department of Electrical Engineering, Universityof South Florida, Tampa, FL 33620 USA, and also with the Department ofElectrical and Electronics Engineering, Istanbul Medipol University, Istanbul34810, Turkey (e-mail: [email protected]).

This article presents an innovative telecommunicationstraining that is designed to cultivate equipped telecommunica-tion engineers by instilling the following abilities:

• To identify, formulate, and solve telecommunication sys-tems’ problems by applying principles of mathematics,digital signal processing (DSP), electromagnetic (EM)wave propagation, and communication theory.

• To apply these fundamental concepts to design andtest spectral/energy-efficient advanced telecommunicationsystems considering a wide variety of system scenarios,channel conditions, and hardware limitations.

• To present designs and document outcomes taking adiverse audience into account.

The training emphasizes hands-on experience and focuses onhardware layers of the open systems interconnection (OSI)model [3]. At least a senior-level standing in electrical engi-neering is required for the proposed training. Not only studentsbut also industry professionals who are looking to expand theirunderstanding of telecommunications are targeted. Althoughthere exist several courses considering either a particulartechnology [4]–[6] or a teaching method [7], [8], the proposedtraining covers various telecommunication technologies andintegrates many modern teaching methods such as gamifiedmicro-tasks and novel doubly dispersive channel emulators.The foundations of the suggested training were laid in [9],and the training is rebuilt by including emerging concepts,contemporary teaching methods, and futuristic projects overthe last decade.

II. MODERN TEACHING METHODOLOGIES

Comprehending certain subjects such as telecommunica-tions is very challenging due to their highly abstract nature.The classical theoretical training prevents observing the imme-diate relationship between cause and effect. Also, theoreticalknowledge without practice is destined to perish. A completeunderstanding can be achieved by an interactive learning expe-rience [10], [11] as shown in Fig. 1. The proposed telecommu-nication engineering training is structured to modernize sucha well-proven methodology.

A solid design builds on a good understanding of theoreticalconcepts. However, telecommunication systems exhibit numer-ous non-linear behaviors that make them difficult to modelwith closed-form expressions. Therefore, numerical modelsare widely used to assist in the evaluation and visualiza-tion of such complex systems. Trainees can manipulate thesystem and sub-system parameters independently and grasp

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their individual effects using various numerical tools. Theseskills are especially critical in their professional career sincetroubleshooting problems with such tools are easier thanfixing them in the hardware prototyping stage. Nonetheless,the validity of the aforementioned models is limited by theassumptions. Therefore, theoretically and numerically verifieddesigns must also be implemented in hardware and testedunder various channel conditions and realistic scenarios. Thehardware implementation can be achieved practically usingflexible radio platforms. Also, it should be pointed out that thenumerical and hardware implementations provide a convenientway for trainees to design telecommunication systems bythemselves and assist reinforced learning.

The fundamental concepts of hardware layers are mod-ularized and taught separately to examine each sub-systemrigorously. In light of the discussions above, an ideal trainingshould integrate theory, numerical modeling, and hardwareimplementation to train future telecommunication engineerswell. Therefore, each training module starts with a theoreticaldiscussion, followed by numerical analysis, and is completedwith hardware implementation in the laboratory. The labora-tory experiments feature telecommunication devices that areused daily such as smartphones and FM radio receivers tointerest trainees. Furthermore, gamified micro-tasks motivatesthem and establishes confidence in this challenging field. Thedetails of each module are given in the following section.At the end of each module, trainees are expected to de-liver a technical report summarizing their key observations.These reports allow receiving immediate feedback regardingtrainees’ progress and help them keep on track throughoutthe fundamental training phase. Upon successful completionof this phase, trainees are examined, and they proceed to theindependent project development phase to demonstrate theirvast proficiency on the topic.

III. DESIGN OF A TELECOMMUNICATION ENGINEERINGTRAINING

The proposed training teaches telecommunications withan emphasis on physical, data link, and network layers.The training content presents the journey of bits throughtelecommunication systems as depicted in Fig. 2. An instructormust compose the teaching environment carefully to deliver

this content effectively. Once the teaching environment isestablished, the fundamental training and independent projectdevelopment phases can be conducted. The total trainingduration depends on the audience. For example, the trainingis offered to students in 15 weeks, whereas the training isdelivered to industry professionals on various extents. A goodrule of thumb would be to allocate 2/3 of the fundamentaltraining period for the independent project development phase.

A. The composition of a Telecommunication Teaching Envi-ronment

The theoretical content and numerical modeling can betaught either in a conventional computer laboratory or re-motely. On the other hand, the hardware implementationrequires a flexible radio platform that consists of software-defined radio (SDR) capable transmitter and receivers alongwith the modular RF front-end and configurable channel emu-lators. A basic SDR test-bed includes a vector signal generator(VSG), a vector signal analyzer (VSA), and a computer thatruns telecommunication system design and analysis tools aswell as cables/antennas as shown in Fig. 3. A VSG cangenerate signals using various digital modulation techniquesand baseband pulse shapes. Also, it can multiplex them invarious domains such as time, frequency, and code to obtainstandard and custom waveforms. These waveforms can eitherbe generated internally using the VSG in standalone operationor externally using the computer, and are conveyed to VSAs.A VSA has the ability to demodulate the standard and customsignals in a standalone mode similar to a VSG. Also, itcan convey the in-phase and quadrature (IQ) samples of thereceived signal to a computer for processing. The interactionbetween a computer and VSGs/VSAs is an excellent mech-anism for teaching, studying, and analyzing the current andupcoming telecommunication systems.

The system design, scenarios, and channel conditions canbe enriched further by extending the test-bed with mobiletransceivers, modular RF front-end, and channel emulationtools as presented in Fig. 4. IQ modems, digital to analogconverters (DACs), analog to digital converters (ADCs), mix-ers, voltage-controlled oscillators (VCOs), power amplifiers(PAs), band-pass filters (BPFs), cables, and antennas are someof the critical RF front-end components of telecommunicationsystems. Testing and measuring a telecommunication systemusing a modular RF front-end provides the ability to analyzethe function and effect of each component separately. In ad-dition, mobile transceivers allow emulating various scenariossuch as cellular hand-off and positioning. For high accuracy re-quirements, handheld VSGs and VSAs are preferable, whereasan abundance of low-cost SDR hardware is more convenientfor experienced trainees to emulate applications involving net-working and interference management. Furthermore, diversechannel conditions can be mimicked via reverberation andanechoic chambers, unmanned aerial vehicles (UAVs), andmetal fans [12]. The frequency selectivity of the channelis controlled through the use of chambers, whereas timeselectivity is managed using multi-speed fans.

DEMIR et al.: AN INNOVATIVE TELECOMMUNICATIONS TRAINING THROUGH FLEXIBLE RADIO PLATFORMS 3

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Fig. 3. Basic SDR test-beds each consisting of a vector signal generator(VSG), a vector signal analyzer (VSA), a computer, and cables/antennas.

B. Fundamental Training Phase

Basic telecommunication concepts can be taught in eightmodules as numbered in Fig. 2. Also, the final moduleadapts trainees to contemporary telecommunication systems.A detailed description is provided in the training website1,and the key components of these modules are summarized asfollows:

1) Introduction to the Basic Telecommunication Concepts:In this module, the theoretical aspects of the concepts thatwill be covered throughout the training are introduced. Also,a transceiver is modeled numerically to present the completepicture of a telecommunication system. First, text messagesfor each test-bed are encoded to bits, modulated, pulse-shaped,and multiplexed into different bands in the presence of additivewhite Gaussian noise by the instructor. The waveforms aresupplied to trainees with combinations of various RF impair-ment (i.e., frequency offset, phase noise, and PA nonlinear-ities) levels and signal to noise ratios (SNRs). Trainees arerequired to down-convert the signals and develop baseband

1http://wcsp.eng.usf.edu/courses/wcsl.html

Fig. 4. A flexible radio platform that features mobile SDR equipments,modular RF front-end, and configurable channel emulators.

receiver algorithms to complete the gamified microtask ofthis module, which is detecting individualized transmittedmessages. Also, trainees assess the performance through theobservation of bit error rate (BER) and several diagrams suchas constellation, IQ polar, and eye. The benefit of this moduleis twofold. First, trainees get familiar with the identificationof telecommunication systems’ problems. Second, traineesbecome acquainted with utilizing numerical tools to designand analyze telecommunication systems.

2) Introduction to the Basic SDR Test-bed: The primaryobjective of this module is to familiarize trainees with abasic SDR test-bed. Trainees generate standard single-carrierand multi-carrier waveforms at the VSGs and assess their


performances using the built-in functions of the VSAs alongwith the corresponding computer software. The concepts thatare theoretically and numerically covered in the first moduleare implemented in the hardware. The instructor allocates adifferent portion of the ISM band to each test-bed, and traineespractice transceiving custom telecommunication signals. Notonly the signals that are generated by VSGs but also overthe air signals such as FM, Wi-Fi, and PCS are analyzedin this module. Observing the FM radio spectrum intereststrainees and relates the taught concepts to daily life. Also,the burst transmission structure in ISM and PCS bands uponWi-Fi and cellular calls is demonstrated. In the last part ofthe module, the received signal at VSA is downloaded to acomputer, and spectro-temporal characteristics are analyzedusing numerical tools. This part is especially important toillustrate the interconnection between the components of abasic SDR test-bed.

3) Digital Modulation: Trainees commence the telecom-munication system design by mapping bits to symbols afterthe overview in the first two modules. The theory part ofthe module teaches the purpose of digital modulation and itslimiting factors such as SNR and peak-to-average power ratio(PAPR). In the numerical and hardware implementation parts,various modulation schemes are demonstrated using built-infunctions and characterized in terms of power efficiency, spec-tral efficiency, and ease of implementation. The analyses startwith the throughput comparison of BPSK and higher-orderQAM and PSK modulation schemes as a function of SNRto demonstrate the trade-off between spectral and energy effi-ciency. This trade-off is made clear through the observation oferror vector magnitude (EVM), IQ polar diagram, eye diagram,and power CCDF curve. After initial characterization, alter-native modulation schemes such as π/2-BPSK, π/4-DQPSK,OQPSK, and MSK that enhance PAPR to overcome hardwarelimitations at the expense of implementation complexity aredemonstrated and examined. After trainees comprehend thedistinguishing characteristics of various digital modulationschemes, the instructor transmits a signal, and trainees attemptto figure out the digital modulation scheme blindly. Traineesunderstand the motivation behind the existence of variousdigital modulation schemes and link adaptation to channelconditions in this module.

4) Baseband Pulse Shaping: The objective of this moduleis to study the impact of baseband pulse shaping filters, whichmap digitally modulated symbols into waveforms, on telecom-munication system performance. The discussions take off withorthogonal raised-cosine (RC) filters. Trainees alter the roll-offparameter that controls the spectro-temporal characteristics,and they observe changes in the spectrum, time envelope,power CCDF curve, IQ polar diagram, and eye diagram.Furthermore, the performance of the RC pulse shaping filter atthe transmitter side is compared with using root-raised-cosine(RRC) pulse shaping filter at both transmitter and receiver, andsuperiority of matched filtering is demonstrated. Also, an RRCpulse-shaped signal is transmitted without matched filteringat the receiver, and the presence of inter-symbol interferenceis pointed out. Once trainees are accustomed to the non-orthogonality in the filter design, the discussion continues with

Gaussian pulse shaping filters that are preferred due to theirspectral confinement. The similarity between the bandwidth-time (BT) product of Gaussian pulse shaping filters and theroll-off factor of RC pulse shaping filters are pointed out. GSMsignals with different BT products are generated, and their per-formances are evaluated as similar to RC pulse-shaped signals.After understanding the spectro-temporal characteristics ofbaseband pulse shaping filters, the instructor transmits signals,and trainees predict the filter parameters. The fundamentals forspectral- and energy-efficient design are taught in this module,and robust filter design against RF front-end impairments andmultiple access wireless channel are further elaborated in thefollowing modules.

5) Multiple Accessing: The purpose of this module is toacquaint trainees with resource allocation among multipleusers and to manage resulting interference. Previously, the test-beds share the channel in an FDMA manner. In this module,they get familiarized with other multiple accessing schemessuch as TDMA and CDMA. Initially, GSM signals withvarying relative burst powers for each slot are broadcasted bythe instructor. Each slot is assigned to a certain test-bed alongwith associated relative burst power. Trainees observe theTDMA frame structure and locate their slot. In the followingstage, the instructor transmits various DSSS-CDMA signals byassigning different codes to each test-bed. As the number ofactive codes increases, trainees observe the power CCDF curveand conclude that an increased number of random variablesdegrades PAPR characteristics. Also, a joint time-frequencyanalysis is performed on Bluetooth signals from two smart-phones using the spectrogram. The smartphones’ distances toa VSA are utilized to identify the hopping structure of eachfrequency hopping spread spectrum code.

Upon introducing conventional resource allocation tech-niques, multiple access interference is explained. Adjacentchannel interference (ACI) is demonstrated by transmittingequipower RRC pulse-shaped signals in adjacent bands si-multaneously without a guard band in between. Although thetest-beds can demodulate their signals with slight performancedegradation, they cannot demodulate each others’ signalsproperly due to the near/far effect. In this step, trainees utilizetheir knowledge from the previous module and adjust theRRC roll-off factor to mitigate ACI. In the next stage, test-beds generate single-carrier signals at the same frequency andemulate a co-channel interference scenario. They observed thattheir communication performance significantly degrades sincethere is an insufficient spatial separation between the test-beds.Afterward, one of the test-beds switches to the DSSS scheme,and it is demonstrated that spread spectrum systems are morerobust against narrowband interference. This module integratespreviously learned concepts and improves multi-dimensionalsignal analysis skills.

6) RF Front-end: Teaching the functionalities and char-acteristics of critical RF front-end components is the coreobjective of this experiment. In the first stage of this module,the instructor informs trainees on IQ modems and familiarizethem with various impairments using the internal IQ modulatoron VSGs. IQ gain imbalance, quadrature offset, and DC offsetare intentionally introduced, and their effect on IQ polar


diagram, eye diagram, and EVM are exhibited. Following thisstage, quantization effects are demonstrated by connecting anexternal DAC with various resolutions to VSGs and alteringthe dynamic range of VSAs. Trainees observe the resultsof quantization errors such as spectral regrowth, increase inEVM, interpolation issues in eye and IQ polar diagrams.Afterward, the analog signal is conveyed to an upconverterunit that consists of a mixer and a VCO to shift the basebandsignal to IF or RF. Trainees compare the stability of low-endstandalone VCOs’ output with that of VSGs. The referencesignals generated by both VCOs are passed through mixersfor upconversion. It is demonstrated that low-end standaloneVCOs cannot output stable tones and produce phase noise.

Trainees analyze the effect of nonlinear behavior of mixersand PAs. First, they observe the spectrum while operating thePA in the linear region. Hence, the harmonics generated onlyby the mixer are presented. Afterward, the transmitted poweris gradually increased, and power CCDF curve, EVM, IQ polardiagram, and spectrum are observed. It is demonstrated thatincreasing the transmit power beyond the hardware limitationsdoes not increase SNR. BPFs are provided to suppress har-monics caused by both components. Furthermore, PAPR isreduced by using digital modulation techniques that omit zero-crossings and utilizing RRC pulse shapes with a higher roll-offfactor. Thus, trainees understand both the inconveniences ofthese devices and techniques to cope with their disadvantages.Also, this module provides them an opportunity for building acomplete RF front-end by connecting all the aforementionedcomponents.

7) Propagation Channel: The purpose of this module isto present fundamental EM wave propagation concepts. Thechannel imposes various effects on EM waves such as distanceand frequency-dependent path loss, large scale fading (i.e.,shadowing), and small scale fading (i.e., delay spread andDoppler spread). In the first stage, the distance- and frequency-dependent characteristics of the path loss are depicted bymeasuring the signal with different antenna separations atdifferent frequencies. Trainees sweep the FM band and recordthe received power levels of various stations. They obtainthe transmit power, antenna height, and distance informationonline. Afterward, a simple statistical path loss model isderived considering the measurements from the stations withthe same parameters. Also, shadowing is demonstrated bypointing out the variation around the path loss.

Small scale fading can originate from two phenomena;namely, delay spread and Doppler spread. In the second stage,a reverberation chamber is used to control the delay spreadamount in an indoor environment. Trainees alter the trans-mission bandwidth, and they observe a frequency selectivechannel when the signal bandwidth exceeds the coherencebandwidth of the channel. It is challenging to demonstratemobility in an indoor environment. Either the transceiver orthe environment must be mobilized. A multi-speed metal fan isutilized to create the variation in time. Trainees place a metalfan in between two antennas and operate it at different speedswhile monitoring the spectrogram. Furthermore, a doubly-dispersive channel is emulated by moving the fan inside thereverberation chamber [12], [13]. Finally, trainees apply the

concepts that are discussed in the previous modules to designtelecommunication systems robust against channel effects. Forexample, the symbol rate is decreased to elevate immunity todelay spread, whereas it is increased to boost resistance toDoppler spread. Furthermore, the RRC roll-off factor is raisedto improve the performance in both spreads with a penalty ofdegraded spectral localization.

8) Receiver Design: The objective of this module is de-signing a complete digital baseband receiver. The instructortransmits a BPSK modulated TDMA frame. The frame con-sists of individualized messages following different repeatedm-sequences for each test-bed. Trainees capture the signal andrecord it for offline processing. They start with the coarse timesynchronization step to pinpoint the position of their desiredmessage. Since two m-sequences are appended back to back,their autocorrelation gives a rough estimate of the allocatedslot beginning. Upon the coarse time synchronization step,the frequency offset amount is estimated using the constantdelay between the consecutive m-sequences. The estimatedfrequency offset is compensated for the frequency synchro-nization. Then, fine time synchronization is performed bycross-correlating the local m-sequence copy with the frequencyoffset compensated signal. Trainees downsample the signal atthe best sampling locations using the fine time synchronizationinformation. Afterward, channel estimation must be carriedout to compensate for the channel effect. The m-sequence ofthe received signal is compared with the local m-sequencecopy in order to estimate the wireless channel. The phase andamplitude of the received signal are corrected upon estimation.In the final stage, digital demodulation is performed, and esti-mated bits are mapped to characters to reveal the transmittedinformation. Trainees are thrilled to be able to demodulatea physical signal similar to their daily devices. This modulefinalizes the modules that are pointed out in the functionaldiagram on Fig. 2 and demonstrates a complete picture of abasic single-carrier communication system.

9) OFDM: The main features of OFDM modulation arestudied in the last training module. The instructor suppliestrainees with a cyclic prefix (CP)-OFDM transmission scriptalong with the VSG and VSA connection libraries. In the firststage, trainees are expected to develop their OFDM basebandreceiver algorithms similar to the previous module. Sincethere is no m-sequence in the frame, CP is used for timeand frequency synchronization. Trainees repeat the hardwareimplementation steps of RF front-end and propagation channelmodules for multi-carrier communication after the receiverdesign. FFT size, number of active subcarriers, CP length,and modulation order are altered in each step, and their effecton the telecommunication system performance is analyzedthrough power CCDF curve, constellation, and spectrum.Also, they compare the impairments for single-carrier andmulti-carrier communication schemes and point out the maindifferences. This module combines all the concepts that arecovered in this training within the perspective of an advancedmodulation scheme that is used in current cellular and Wi-Fisystems.


(a) (b) (c)

(d) (e) (f)

Fig. 5. Sample projects: (a) PIC driven SDR; (b) in vivo channel characterization [14]; (c) object identification through channel features; (d) angle-of-arrivalestimator for UAVs using a MIMO capable low-cost SDR; (e) MIMO front-end design; (f) adaptive beamformer for mmW [15].

C. Independent Project Development Phase

Trainees become ready to pursue independent projects uponthe completion of the fundamental training phase. Althoughnovelty is not enforced, it is highly encouraged. Consideringthe last 50+ projects that are completed under the authors’supervision, the feasible and educational projects are categor-ically summarized to inspire prospective trainees as follows:

1) Software-defined radio (SDR): The expertise acquiredwith the higher-end SDR platforms in the fundamental trainingphase equips trainees with the ability to build their low-costSDRs. These projects are especially suitable for embeddedsystem developers seeking to implement the Internet of Thingstransceivers. Fig. 5a depicts an exemplary PIC driven FSKtransmitter with its RF front-end. The budget-limited SDRhardware comes with the price of excessive RF front-endimpairments. Trainees must also develop advanced basebandalgorithms to mitigate IQ impairments, PA nonlinearities, andlow-resolution DAC/ADC quantization issues.

2) Wireless channel: The fundamental training phase pro-vides the ability to comprehend basic features of conventionalcellular and WiFi channels. Trainees with strong propagationengineering backgrounds may characterize and model differentenvironments such as the promising in body channel (Fig.5b [14]). Furthermore, advanced channel features can beextracted to determine line-of-sight/non-line-of-sight condi-tions or to design an object identifier via machine learning(Fig. 5c). Location services driven by channel propertiesare also compelling projects. Triangular positioning, channel-based authentication, distance and angle-of-arrival estimation(Fig. 5d) techniques are exemplary candidates. Moreover, thenovel doubly-dispersive channel emulators [12], [13] used inthe fundamental training phase were originally designed andimplemented as trainee projects.

3) Wireless channel counteractions: After obtaining a well-understanding in channel characteristics, trainees can exploitthem to improve telecommunication systems further. For ex-ample, MIMO systems are designed to take advantage ofspatial diversity. Trainees with antenna and RF circuit designexperience prefer MIMO front-end design and manufacturing(Fig. 5e), whereas trainees with solid communication theorybackground favor MIMO power allocation, channel estimation,and compensation projects. Furthermore, the mmW channel,which will be deployed in 5G, can be studied as well. Forinstance, the mmW blockage issue is dealt with an adaptiveantenna beamwidth implementation as shown in Fig. 5f [15].

4) Signal intelligence: Trainees with DSP and communi-cation theory backgrounds may utilize their extensive knowl-edge on multi-dimensional signal analysis, and communica-tion channel to pursue signal intelligence applications. Theseapplications include non-data aided blind receivers whichestimate various parameters such as symbol rate, modulationtype, and pulse shaping filter parameters in the presence ofRF front-end and channel impairments. Furthermore, traineescan conceal the transmitted signal to prevent eavesdroppingusing various single- and multi-antenna physical layer securitytechniques such as artificial noise transmission. Also, traineesmay utilize channel-based authentication methods to identifythe legitimate transmitter as well.

5) Multiple access and interference management: The fun-damental training phase mostly covers the centralized andorthogonal multiple accessing schemes. Alternative schemessuch as cognitive radio (CR) and non-orthogonal multipleaccess (NOMA) attract trainees with data link layer interestand cultivate numerous projects. For example, the spectrum isutilized opportunistically in CR, and trainees avoid interferingthe primary user. Furthermore, non-contiguous frequency re-sources can be aggregated in these projects. NOMA is another


spectral-efficient resource utilization scheme and can be real-ized with multi-user detection, blind source separation, andinterference cancellation algorithms. Moreover, trainees maymanage self-interference and develop full-duplex communica-tion schemes to improve the capacity of telecommunicationsystems.

6) Standards: Trainees can improve their expertise intelecommunication systems by partially implementing hard-ware layers of various standards such as 3G/4G/5G cellular,IEEE 802.11, Bluetooth, and stereo FM. In addition, thoseinterested in network layer may realize vertical handoff mecha-nisms to switch between different standards in a heterogeneousnetwork scenario. Mobile SDR equipment is essential in theseprojects. Moreover, trainees can asses new technologies forfuture standards. For example, various waveforms might beimplemented to evaluate their performances in realistic sce-narios considering diverse channel conditions, multiple accessinterference, and RF front-end impairments.

IV. TRAINEE IMPROVEMENT

The fundamental training phase, which integrates theory,numerical modeling, and hardware implementation, leads tocompetent telecommunication engineers with a solid educa-tion. Trainees who completed the training are distinguishedin their further telecommunication education and career. Theiracademic success was tracked, and their superiority to thosewho had not completed this training is revealed in both [9, Ta-ble V] and Table I. Student final scores in telecommunications-related courses from 2016 to 2019 are analyzed. Seventystudents who have taken this training succeed better in thelisted courses than 330 students who have not as presentedin Table I. Also, [9, Table IV] points out that they feel moreconfident with telecommunication system design and analysisafter the training.

The independent project development phase requirestrainees to acquire and apply new knowledge as neededwithout well-defined instructions and sharpens their analysisand synthesis skills. Also, it promotes teamwork and gener-ates synergistic engineers. Trainees improve their presentationskills by demonstrating their projects effectively to a widerange of audience that includes undergraduate students, grad-uate students, faculty, and industry professionals. Discussionsthat take place during presentations and feedback receivedafterward are reportedly beneficial for professional interviews.The documentation of projects benefits technical writing skills.Furthermore, notable projects are encouraged for publication,and scientific interest among trainees is cultivated.

Finally, the instructors who are assisting trainees throughouttheir telecommunication education journey also benefit fromtutoring, which completes their mastery as pointed out in Fig.1.

V. CONCLUSIONS

The industry and academia require well-trained telecommu-nication engineers. The proposed training is a well-establishedguideline to educate outstanding engineers and to build abridge between these two institutions by integrating theoretical

TABLE IACADEMIC SUCCESS COMPARISON

Course TitleGrade

(w/o the Training) Grade

(with the Training) Performance Improvement

Broadband Communication Networks

84.19% 84.30% 0.13%

Digital Communication Systems 68.41% 81.43% 19.03%

Mobile and Personal Communication

50.29% 74.35% 47.84%

OFDM and Beyond 49.06% 60.33% 22.97%

Wireless Mobile Computingand Security

91.53% 94.23% 2.95%

Wireless Network Architecture and Protocols

83.45% 89.04% 6.70%

Wireless Sensor Networks 90.11% 90.50% 0.43%

* The reader is referred to below website for a detailed description of the courses listed.https://www.usf.edu/engineering/ee/

proficiency, numerical modeling skills, and hands-on expe-rience. The provided array of skills as well as professionalqualities help trainees to succeed in their professional journeysand to design future generation telecommunication systems.Other institutions that are willing to set up a similar trainingcan profit from the experiences shared in this article. Espe-cially, the improvement of trainees confirm the effectivenessand make the proposed training a candidate for the flagshiptraining of telecommunication education.

ACKNOWLEDGMENT

The authors would like to thank former trainees: J. Olivo,A. Menon, M. F. Kucuk, N. Soulandros, and G. Gillespie fortheir outstanding projects that are presented in Fig. 5. Also, wewould like to thank USF professors: R. D. Gitlin, N. Ghani, S.Morgera, and Z. Lu for their courteously supplied academicsuccess statistics that are demonstrated in Table I.

REFERENCES

[1] S. Parkvall, E. Dahlman, A. Furuskar, and M. Frenne, “NR: The new 5Gradio access technology,” IEEE Communications Standards Magazine,vol. 1, no. 4, pp. 24–30, Dec 2017.

[2] D. Consonni and M. T. M. Silva, “Signals in communication engineeringhistory,” IEEE Trans. Educ., vol. 53, no. 4, pp. 621–630, Nov 2010.

[3] Information technology – Open Systems Interconnection – Network ser-vice definition, International Organization for Standardization StandardISO/IEC 8348:2002, Rev. 3, Nov. 2002.

[4] W. T. Padgett, B. A. Black, and B. A. Ferguson, “Low-frequencywireless communications system-infrared laboratory experiments,” IEEETrans. Educ., vol. 49, no. 1, pp. 49–57, Feb 2006.

[5] F. A. Cassara, “Wireless communications laboratory,” IEEE Trans.Educ., vol. 49, no. 1, pp. 132–140, Feb 2006.

[6] Y. Linn, “An ultra low cost wireless communications laboratory foreducation and research,” IEEE Trans. Educ., vol. 55, no. 2, pp. 169–179, May 2012.

[7] H. Aliakbarian, P. J. Soh, S. Farsi, H. Xu, E. H. E. M. J. C. V.Lil, B. K. J. C. Nauwelaers, G. A. E. Vandenbosch, and D. M. M.-P. Schreurs, “Implementation of a project-based telecommunicationsengineering design course,” IEEE Trans. Educ., vol. 57, no. 1, pp. 25–33,Feb 2014.

[8] S. M. Berber and K. W. Sowerby, “Visual presentation of abstract the-oretical concepts using animations in communication systems courses,”Computer Applications in Engineering Education, vol. 26, no. 1, pp.49–61, 2018.

[9] S. Güzelgöz and H. Arslan, “A wireless communications systemslaboratory course,” IEEE Trans. Educ., vol. 53, no. 4, pp. 532–541,Nov 2010.


[10] E. Dale, Audio-visual methods in teaching, 3rd ed. New York: Holt,Rinehart & Winston, 1969.

[11] N. Hoic-Bozic, V. Mornar, and I. Boticki, “A blended learning approachto course design and implementation,” IEEE Trans. Educ., vol. 52, no. 1,pp. 19–30, Feb 2009.

[12] S. Güzelgöz, S. Yarkan, and H. Arslan, “Investigation of time selectivityof wireless channels through the use of RVC,” Measurement, vol. 43,no. 10, pp. 1532–1541, 2010.

[13] A. B. Kihero, M. Karabacak, and H. Arslan, “Emulation techniques forsmall scale fading aspects by using reverberation chamber,” IEEE Trans.Antennas Propag., vol. 67, no. 2, pp. 1246–1258, Feb 2019.

[14] A. F. Demir, Q. H. Abbasi, Z. E. Ankarali, A. Alomainy, K. Qaraqe,E. Serpedin, and H. Arslan, “Anatomical region-specific in vivo wire-less communication channel characterization,” IEEE J. Biomed. HealthInform., vol. 21, no. 5, pp. 1254–1262, Sept 2017.

[15] S. Dogan, M. Karabacak, and H. Arslan, “Optimization of antennabeamwidth under blockage impact in millimeter-wave bands,” in Proc.2018 IEEE 29th Annu. Int. Symp. Personal, Indoor and Mobile RadioCommun., Bologna, IT, Sep. 2018, pp. 1–5.

Ali Fatih Demir (S’08) received the B.S. degree inelectrical engineering from Yıldız Technical Univer-sity, Istanbul, Turkey, in 2011 and the M.S. degreesin electrical engineering and applied statistics fromSyracuse University, Syracuse, NY, USA in 2013.He is currently pursuing the Ph.D. degree as amember of the Wireless Communication and SignalProcessing (WCSP) Group in the Department ofElectrical Engineering, University of South Florida,Tampa, FL, USA. His current research interestsinclude PHY and MAC aspects of wireless com-

munication systems, in vivo wireless communication systems, and signalprocessing/machine learning algorithms for brain-computer interfaces.

Berker Peköz (GS’15) received the B.S. degree inelectrical and electronics engineering from MiddleEast Technical University, Ankara, Turkey in 2015,and the M.S.E.E. from University of South Florida,Tampa, FL, USA in 2017. He was a Co-op Intern atthe Space Division of Turkish Aerospace Industries,Inc., Ankara, Turkey in 2013, and a Summer Internat the Laboratory for High Performance DSP &Network Computing Research, New Jersey Instituteof Technology, Newark, NJ, USA in 2014. He iscurrently pursuing the Ph.D. at University of South

Florida, Tampa, FL, USA. His research is concerned with standard compliantwaveform design and optimization. Mr. Peköz is a member of Tau Beta Pi.

Selçuk Köse (S’10–M’12) received the B.S. degreein electrical and electronics engineering from BilkentUniversity, Ankara, Turkey, in 2006, and the M.S.and Ph.D. degrees in electrical engineering from theUniversity of Rochester, Rochester, NY, USA, in2008 and 2012, respectively. He was an AssistantProfessor of Electrical Engineering at the Universityof South Florida, Tampa, FL, USA. He is currentlyan Associate Professor of Electrical and ComputerEngineering at University of Rochester, Rochester,NY, USA. His current research interests include

integrated voltage regulation, 3-D integration, hardware security, and greencomputing. Dr. Köse was a recipient of the NSF CAREER Award, theCisco Research Award, the USF College of Engineering Outstanding JuniorResearcher Award, and the USF Outstanding Faculty Award. He has served onthe Technical Program and Organization Committees of various conferences.He is currently an Associate Editor of the World Scientific Journal of Circuits,Systems, and Computers and the Elsevier Microelectronics Journal.

Hüseyin Arslan (S’95–M’98–SM’04–F’15) re-ceived the B.S. degree in electrical and electronicsengineering from Middle East Technical University,Ankara, Turkey in 1992, and the M.S. and Ph.D.degrees in electrical engineering from SouthernMethodist University, Dallas, TX, USA in 1994 and1998, respectively. From January 1998 to August2002, he was with the research group of EricssonInc., Charlotte, NC, USA, where he was involvedwith several projects related to 2G and 3G wirelesscommunication systems. He is currently a Professor

of Electrical Engineering at the University of South Florida, Tampa, FL, USA,and the Dean of the College of Engineering and Natural Sciences at the Istan-bul Medipol University, Istanbul, Turkey. His current research interests are on5G and beyond, waveform design, advanced multiple accessing techniques,physical layer security, beamforming and massive MIMO, cognitive radio,dynamic spectrum access, interference management (avoidance, awareness,and cancellation), co-existence issues on heterogeneous networks, aeronautical(high altitude platform) communications, millimeter-wave communicationsand in vivo communications. He has served as technical program committeechair, technical program committee member, session and symposium orga-nizer, and workshop chair in several IEEE conferences. He is currently amember of the editorial board for the IEEE Communications Surveys andTutorials and the Sensors Journal.

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