DIGITAL SIGNAL PROCESSING ORIENTED

ELECTRONIC COMMUNICATION

ENGINEERING APPLICATIONS AND

PRACTICES

Qinghe Wang*

• Jiangsu College of Tourism, Yangzhou, Jiangsu, 225000, China

•E-mail: qinghewang202388@163.com

Reception: 4 January 2024 | Acceptance: 24 January 2024 | Publication: 12 February 2024

Suggested citation:

Wang, Q. (2024). Digital Signal Processing Oriented Electronic

Communication Engineering Applications and Practices. 3C TIC.

Cuadernos de desarrollo aplicados a las TIC, 13(1), 96-115. https://doi.org/

10.17993/3ctic.2024.131.96-115

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ABSTRACT

This paper first describes the applications of digital signal processors in software

radio, speech compression coding, modems and GPS systems, demonstrating the

versatility of digital signal processors in practical communication systems. Next, digital

signal processing oriented electronic communication practices are presented in the

system design section to design high performance communication systems for

specific communication needs and environmental conditions. The digital signal

processing platform used in the platform architecture is optimized for signal

processing and data transmission. The BER is 0.008% when the signal-to-noise ratio

is -10 dB. The time complexity of digital signal processing is 7.2 ms when the number

of communication nodes is 1000. It shows that digital signal processing oriented

electronic communication engineering is important for improving the performance,

reliability and efficiency of communication systems.

KEYWORDS

Digital signal processing; speech compression; GPS system; electronic

communication; signal-to-noise ratio

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INDEX

ABSTRACT .....................................................................................................................2

KEYWORDS ...................................................................................................................2

1. INTRODUCTION .......................................................................................................4

2. APPLICATION OF DIGITAL SIGNAL PROCESSOR IN COMMUNICATION

ENGINEERING .........................................................................................................5

2.1. Applications in Software Radio ..........................................................................5

2.2. Applications in speech compression coding ......................................................6

2.2.1. Principles of Composition ............................................................................6

2.2.2. Signal operating modes ...............................................................................7

2.3. Applications in modems .....................................................................................8

2.4. Application in GPS systems ...............................................................................9

3. DIGITAL SIGNAL PROCESSING ORIENTED ELECTRONIC COMMUNICATION

PRACTICES .............................................................................................................9

3.1. System design ....................................................................................................9

3.2. Platform structure .............................................................................................10

4. ELECTRONIC COMMUNICATION VERIFICATION FOR DIGITAL SIGNAL

PROCESSING ........................................................................................................13

4.1. Performance metrics validation ........................................................................13

4.2. Algorithm efficiency analysis ............................................................................15

4.3. System Stability and Reliability Testing ............................................................16

4.4. Environmental and Disturbance Testing ...........................................................17

5. CONCLUSION ........................................................................................................18

6. DISCUSSION ..........................................................................................................18

ABOUT THE AUTHOR .................................................................................................18

FUNDING ......................................................................................................................19

REFERENCES ..............................................................................................................19

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1. INTRODUCTION

The research on the application and practice of electronic communication

engineering oriented to digital signal processing is at the forefront of the current

scientific and technological development, integrating the latest achievements of

electronic engineering, communication technology and computer science [1]. With the

rapid development of digital technology, digital signal processing has become the core

technology in the field of electronic communication, which plays a key role in many

aspects such as speech, image processing, wireless communication and data

compression [2]. The rapid progress in this field, especially the breakthroughs in

mobile communication, satellite communication and network technology, has brought

revolutionary changes to electronic communication engineering [3]. The high

efficiency, flexibility and powerful functions of digital signal processing technology

provide the possibility of processing a large number of complex communication

signals, and at the same time bring new challenges, such as the need for high-speed

signal processing, signal quality assurance and the implementation of complex

algorithms [4]. Therefore, studying the application and practice of digital signal

processing in electronic communication engineering is not only crucial for the

development of the theory, but also has a far-reaching impact on practical engineering

applications [5]. With the rise of the Internet of Things, smart devices and 5G

communication technology, the research and exploration of this field will be more

urgent, foreshadowing the future development direction and application prospects of

communication technology [6].

The density matrix of subsystems in reacting complexes is discussed by

Nalewajski, R. F and is used to describe the entanglement phenomena occurring in

donor-acceptor systems including molecular fragmentation and electronic

communication [7]. Han, D et al. activated the molybdenum disulphide MoS2 by

doping it with palladium and achieved a phase transition to the stable 1T phase. The

study was also verified using Raman spectroscopy. The prepared Bi/Pd-MoS2

catalysts exhibited excellent electrochemical hydrogen precipitation performance in

acidic medium [8]. Toyoshima, M discussed the concept of utilizing smaller and less

power consuming on-board devices for broadband and high capacity

communications. This technique can provide more efficient communication in space

communication and has a wide range of applications [9]. Zhang, L et al. proposed that

conventional wireless communication usually requires digital-to-analog conversion

and frequency mixing to transmit digital information to different users at different

locations. However, spatio-temporal coded digital metasurfaces can encode spatio-

temporal coding matrices over multiple channels and directly transmit digital

information to multiple users at the same time without the need for complex

processing [10]. Tan, M. et al. introduced an optical signal processing technique that

achieves extremely high performance, including high bandwidth and low energy

consumption. This optical signal processor can process 17 Terabits/s of data, is

capable of processing 400,000 video signals simultaneously, and performs 34

different image processing functions such as object edge detection, edge

enhancement, and motion blur processing [11]. He, X et al. stated that although power

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electronics and communication electronics are often regarded as two different

branches of the electrical engineering field. However, both are based on

electromagnetic theory. In addition, electricity is considered as the most common

material-based information carrier. Therefore, power electronics and communication

electronics can be considered together to find new applications and approaches [12].

Huang, C et al. proposed a new approach to construct highly parallel, ultrafast neural

networks using photonic devices to process optical signals in the analog domain, thus

reducing the need for digital signal processing circuits. A silicon photonic electronic

neural network was reported for solving the fiber nonlinearity compensation problem

in submarine fiber optic transmission systems [13]. Niu, Z et al. described the

architecture of this communication system using the microwave band to provide

multiple signal carriers that are converted to 220GHz channels, thus reducing the

need for high sampling rate analog-to-digital converters. The system consists of a set

of 220 GHz solid-state transceivers including two signal carriers and two basebands

to support 4 GSPS analog-to-digital converters. A 16QAM modulation is used [14].

Digital signal processors are used to process and optimize signals to improve the

performance of communication systems. This paper firstly describes the application of

digital signal processor in communication engineering to realize flexible radio

communication systems through digital signal processing so that they can adapt to

different communication standards and spectrum requirements. The application of

digital signal processing in voice coding can help to achieve efficient data

compression and transmission in order to deliver high quality voice communication

with limited bandwidth. Modems are key components in communication systems and

digital signal processing helps to improve the performance of modems to ensure

reliable data transmission. In digital signal processing oriented electronic

communication practices, system design and platform architecture are carried out to

ensure effective application of digital signal processing in practical communication

engineering.

2. APPLICATION OF DIGITAL SIGNAL PROCESSOR IN

COMMUNICATION ENGINEERING

2.1. APPLICATIONS IN SOFTWARE RADIO

The application of software radio in communication, especially in the 3rd generation

mobile communication has become more and more the focus of research. Digital

signal processor hardware technology and its algorithms are precisely the key to the

realization of software radio, software radio system flexibility openness and tolerance

and other characteristics, mainly through the signal processor as the center of the

general hardware platform and software to achieve [15-16]. Figure 1 shows the

software radio system framework, mainly to complete the radio station internal data

processing modulation and demodulation and coding and decoding work. Due to the

radio internal data flow, filtering frequency conversion and other processing operations

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more often, must use high-speed real-time parallel digital signal processor module, or

special integrated circuits in order to meet the requirements. To complete such a

difficult task, must require hardware processing speed increases, chip capacity

expansion, while requiring algorithms for the processor optimization and improvement.

Figure 1. Software radio system

2.2. APPLICATIONS IN SPEECH COMPRESSION CODING

2.2.1. PRINCIPLES OF COMPOSITION

The purpose of speech data compression is to be able to obtain high quality

speech effects at the lowest possible transmission rate. That is, it is desired that the

speech signal can be transmitted in a channel with a more observable bandwidth with

little or as little degradation in the quality of the speech as possible [17]. Speech

coding systems early used waveform coding methods, also called waveform coding

which essentially follows the Nyquist sampling theorem, adaptive ability to synthesize

better speech quality [18]. But the coding rate is high, the coding efficiency is very low

and parametric coding is different from waveform coding efficient coding method, is

the mechanism of speech generation is mainly on the extracted speech signal

characteristics of the parameters of the coding, can achieve a very low coding rate.

But can only achieve the effect of synthesized speech, voice quality is not as good as

waveform coding for voice processing, the higher the compression rate, the more

complex the coding algorithm, real-time compression is not possible to use logic

circuits to achieve, but also will not be used to achieve a large volume of slow and

high-cost microcomputer. The digital signal processor is a suitable choice, Figure 2 for

the composition of the principle of speech coding, the use of DSP to develop

embedded voice coding and decoding system, it is one of the popularity of the current

research. In the network conference voice communication monitoring systems and

other areas are important components, the use of digital signal processors not only for

the application of voice compression algorithms provide a broad prospect, and make

the system design becomes simple reliability is also greatly improved.

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Figure 2. Components of speech coding

2.2.2. SIGNAL OPERATING MODES

There are four modes of operation during communication, including:

1. The default mode after power-up or reset is the single-frequency signal mode,

with a default value of zero in the frequency control word register [19]. The

default value after power-up or reset defines a safe no-output state that

produces a 0 Hz, 0 phase output signal. The default zero amplitude setup

mode outputs from both the I and O digital-to-analog converters are DC, with

an amplitude corresponding to a medium output current. The user must

program some or all of the 28 registers to obtain the desired output signal. The

value of the frequency control word is determined by the following equation:

(1)

Where is the phase accumulator, in this case 48 bits, the frequency is

expressed in Hz, and the frequency control word, FTW, is a decimal number.

Once a decimal number has been calculated, it must be rounded to the nearest

whole number and then converted to binary format. The basic sine wave DAC

output frequency ranges from DC to 1/2 system clock. The phase is continuous

as the frequency changes, meaning that the new frequency uses the last,

phase of the old frequency as the starting phase.

2. When the frequency shift keying mode is selected, the output frequency of the

DDS is the value of frequency control word register 1 or frequency control word

terminal PIN29. When logic is low on PIN29, select F1, frequency control word

FT W =(DOF*2N)/*SYSCLK

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1, and when logic is high, select F2 frequency control word 2. Frequency

changes are phase-continuous and almost instantaneous.

3. CHIRP mode is also known as pulse FM. Pulse FM can be used with any

sweep, but most Chirp systems use a linear FM sweep. This is a spread

spectrum modulation that allows for processing gain. The user-definable

frequency range FTW1~FTW2, duration, frequency resolution, and sweep

direction can be internally generated linear, monitored and managed by the

electric frequency manager, or externally programmed to generate a nonlinear

sweep.3GN00LD can be pulsed or continuous wave. Non-linear sweeping is

achieved by varying the time step slope counter, and the frequency step delta

frequency word to produce different slopes. delta frequency control word is a

binary complement, positive or negative, which defines the direction of the

CHIRP mode sweep. If the DELTA frequency control word is negative, the

highest bit goes high. If the DELTA frequency control word is negative, the

highest bit is a high level, the frequency is scanned from FTW1 to the negative

direction, and the frequency is decreasing.

2.3. APPLICATIONS IN MODEMS

In a modem, a digital signal processor is used to perform tasks such as modulation

and demodulation, adaptive equalization, and echo cancellation. Figure 3 shows the

operating principle of the demodulator, TMS320C25 has a large storage space and

rich internal resources, so it can support a variety of standard algorithms in the classic

modem, synchronization and timing is the use of the phase discriminator road filter

voltage-controlled oscillator and other components of the phase-locked loop. The DS

has a very high precision internal programmable timer sound quite interface circuit

TLC32044c, and the rate can be fine-tuned with the program 14-bit A/D and D/A

converter. Therefore, the above mentioned by the DSP and other devices constitute

the modulation and demodulation scheme, all operations, including timing and

synchronization can be achieved with software.

Figure 3. Working principle of demodulator

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2.4. APPLICATION IN GPS SYSTEMS

GPS is a non-self-contained navigation and positioning system developed by the

U.S. based on the reception of navigation satellite signals, and this system provides

accurate and continuous two-dimensional position and velocity information to global

users with appropriate receiving equipment [20]. Widely used in various military and

economic fields, along with the promotion and popularization of GPS technology in

various fields of application, the miniaturization of the receiver intelligent and meet the

user needs of the algorithm research are very necessary [21]. Global positioning

system is mainly composed of two parts, the satellite constellation monitoring network

and user receiving equipment by the receiving equipment is different. Mainly includes

the GPS receiver and its antenna processing transmission 3 output, and a power

supply in GPS applications often need to reprocess the data collected by the GPS

receiver, or the use of GPS receivers to provide certain information for the

development of a certain industry within the DSP, small size, high speed, low power

consumption and high reliability characteristics. Suitable for real-time processing of

highly complex GPS signals, with its composition with the OEM board GPS

information system, not only well meet the GPS signal processing in real time and

high complexity, and in the DSP's powerful data processing capabilities of the system

can also be further functionality to expand the clock stops, thereby terminating the

clock pulse sent to the frequency accumulator. The result is to stop sweeping, so that

the output frequency is maintained at the frequency of the hold terminal is valid. After

the holdover is released, the clock is restored and the sweep continues. In the hold

state, the user can change the value of the register, however, the slope counter must

be the original slope to resume work until the count is zero, to load the new slope

count initial value.

Phase shift keying means fast switching between two pre-set 14-bit phase shifts,

and this switching affects both of the AD9852's 2 converters. The logic state at the

BPSK end selects the phase shift, and when it is low, phase 1 is selected, and when it

is high, phase 2 is selected. If more phase shifts are required, monotonic mode should

be selected, and the phase register should be programmed with either a serial or

high-speed parallel bus.

3. DIGITAL SIGNAL PROCESSING ORIENTED

ELECTRONIC COMMUNICATION PRACTICES

3.1. SYSTEM DESIGN

The hardware circuit is mainly composed of two parts: the transmitter side and the

receiver side. The transmitter side is mainly composed of power supply module,

temperature acquisition circuit, microcontroller, wireless transmission module, reset

circuit, clock circuit, etc. The transmitter side is mainly to realize that the real-time

temperature value is converted into a digital signal to be sent to the microcontroller,

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and then the serial port of the microcontroller is transported to the wireless signal

transceiver module to be sent to the receiver side of the system. The receiving end is

shown in Figure 4. To have a power supply module, microcontroller, reset circuit,

keyboard circuit, clock circuit, buzzer alarm, wireless receiver module and LCD

module and other components. Converted to digital signals, transmitted to the

microcontroller, after processing by the microcontroller, the data will be sent to the

LCD display module to display the measured value of the sampling end and the

buzzer alarm module for over-limit alarm.

Figure 4. Receiver side

3.2. PLATFORM STRUCTURE

In order to establish the digital signal processing system of electronic information

engineering integrated practice platform, Figure 5 shows the DSP processor as the

core signal processing unit, integrated man-machine dialogue operation and computer

control of the signal processing platform [22-23]. The whole system is mainly

composed of two parts: computer and DSP processor. Among them, the DSP

processor mainly consists of three parts: memory, interface and real-time channel,

which accepts the operation control of the computer and real-time completion of

different tasks such as storage, processing and transmission of signal data. Computer

to electronic information engineering comprehensive practice, the application of signal

processing system, DSP processor to send back the data for further processing. For

example, digital analysis, waveform display and so on, at the same time, also control

the specific operation of the DSP processor. In this way, through the flexible software

loading of digital signals, you can realize the content of different integrated practice of

electronic information engineering. The basic principles of modulation and

demodulation of the amplitude of the system.

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Figure 5. DSP signal processing unit

On the basis of the above system design, the basic principle of modulation and

demodulation of the system amplitude is shown in Fig. 6.Amplitude keying uses the

amplitude change of the carrier wave to transmit digital information while its frequency

and initial phase remain constant. In 2ASK, the amplitude of the carrier wave has only

two states of change, corresponding to the binary information 0 or 1.

Figure 6. Modulation and demodulation of amplitude control

A common and simplest form of binary amplitude keying is called on-off keying. Its

expression is:

(2)

ook(t) =

{cA cos w

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The general expression for a 2ASK signal is .

In this case, there are usually two types of binary amplitude keying signals

generated, the analog modulation method and the keying method, and the

corresponding modulators are shown in Fig. 7. Fig. 7(a) shows the general analog

amplitude modulation method, which is implemented with a multiplier. Fig. 7(b) is a

digital keying method in which the switching circuit is controlled by s(t). The digital

keying method is used in this paper.

Figure 7. Signal modulator principle

As with the demodulation method for AM signals, there are two basic demodulation

methods for ASK/OOK signals, the incoherent demodulation envelope detection

method and the coherent demodulation synchronization detection method, and the

corresponding block diagram of the receiving system composition is shown in Fig. 8.

Compared with the receiving system for analog signals, a sampling judge box is

added here, which is necessary to improve the receiving performance of digital

signals, and coherent demodulation is used in this paper.

2ASK

(t)=s(t)cos w

(t)=∑

ang(t−nTS

)

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Figure 8. Signal Receiving System Component Box

4. ELECTRONIC COMMUNICATION VERIFICATION

FOR DIGITAL SIGNAL PROCESSING

4.1. PERFORMANCE METRICS VALIDATION

In this paper, in the Malthb environment, the communication node information

transmission collision avoidance simulation analysis, without considering the control,

check redundancy and other data, according to epcglobal company, the proposed

coding standard, by the number of communication node labels from 0 to increase to

2200, randomly formed 95-bit information code. Figure 9 shows the results of time

complexity analysis, when the number of communication node labels is 0, the time

complexity of digital signal processing is 2.5 ms, fiber optic communication is 4.6 ms,

and digital technology is 4.9 ms. digital signal processing performs best. As the

number of communication node tags increases, the time complexity of all three

methods gradually increases. The time complexity of digital signal processing grows

relatively slowly, and fiber optic communication and digitization techniques grow

faster. The time complexity for the number of communication nodes is 1000 is 7.2 ms

for digital signal processing, 14.2 ms for fiber optic communication and 14.89 ms for

digitization techniques. Digital signal processing performs the best at this point.

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Figure 9. Results of time complexity analysis

The selection of the best communication method for different SNR conditions

depends on the specific application requirements and resource budget. Table 1 shows

the results of signal-to-noise ratio comparison of different methods, and in all three

methods, the performance improves as the signal-to-noise ratio increases. At low

signal-to-noise ratios of -10 dB to 0 dB, digital signal processing performs the best

and its performance is higher than the other two methods, and digital signal

processing can process signals more efficiently under low signal-to-noise ratio

conditions. At high signal-to-noise ratios of 35 dB to 40 dB, the performance gap

between the three methods becomes smaller, but digital signal processing is still

slightly ahead. At low signal-to-noise ratios, the performance gap between digital

signal processing and the other two methods is larger, especially at -10 dB signal-to-

noise ratio. It indicates that digital signal processing is the best choice for working at

low signal-to-noise ratios because it performs best under these conditions.

Table 1. Comparison results of signal-to-noise ratio of different methods

Signal-to-Noise

Ratio

Digital signal

processing

Fiber optic

communications

Digitization

technology

-10

2.1

3.9

4.2

-5 2.3 4.1 4.5

0 2.6 4.4 4.8

5 2.9 4.7 5.2

10 3.2 5.0 5.5

15 3.6 5.3 5.9

20 3.9 5.6 6.2

25 4.2 5.9 6.6

30 4.5 6.2 6.9

35 4.8 6.5 7.3

40 5.1 6.8 7.6

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4.2. ALGORITHM EFFICIENCY ANALYSIS

Table 2 shows the efficiency comparison of the three algorithms, where the

resource consumption of the digital signal processing method gradually increases

from 15% to 38% in the same time. It shows that digital signal processing requires

less computational and storage resources to handle the communication task and the

resource consumption gradually increases with time. The resource consumption of

fiber optic communication methods gradually increases over the same period of time,

from 30% to 55%. Although the resource consumption of fiber optic communication is

higher than that of digital signal processing, it starts taking more resources at an

earlier time. The resource consumption of digitization techniques approach increases

from 25% to 46% in the same time period. Although the resource consumption of

digitization techniques is between digital signal processing and fibre optic

communications, it started to take up more resources at an earlier time.

Table 2. Efficiency of three algorithms

Signal-to-Noise

Ratio

Digital signal

processing

Fiber optic

communications

Digitization

technology

-10 2.1 3.9 4.2

-5 2.3 4.1 4.5

0 2.6 4.4 4.8

5 2.9 4.7 5.2

10 3.2 5.0 5.5

15 3.6 5.3 5.9

20 3.9 5.6 6.2

25 4.2 5.9 6.6

30 4.5 6.2 6.9

35 4.8 6.5 7.3

40 5.1 6.8 7.6

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4.3. SYSTEM STABILITY AND RELIABILITY TESTING

In terms of system availability, all three methods have very high availability, above

98%. In terms of BER testing, the average BER of all three methods is very low,

ranging from 1 × 10-61 × 10-6 to 9 × 10-79 ×

10-7 respectively. The pass rates were

also high, all above 98%, indicating that these methods performed well in data

transmission. The immunity test shows that the digital signal processing techniques

have good immunity to interference. The immunity test shows that the digital signal

processing has good immunity to interference with a high level of immunity to

interference and resistance to multipath interference.

Table 3 System stability and reliability results

Test Items Indicator Digital Signal

Processing

Fiber Optic

Communication

Digitization

Technology

System

Availability

(%)

Mean Time

Between Failures

(MTBF)

1500h 2000h 1800h

Mean Time to

Repair (MTTR) 30h 40h 35h

System Availability

(MTBF / (MTBF +

MTTR))

97.4% 98.0% 98.0%

Bit Error Rate

Test

Average Bit Error

Rate (BER) 1×10−61×10−68×10−78×10−79×10−79×10−7

Maximum Bit Error

Rate (BER) 1×10−51×10−57×10−67×10−68×10−68×10−6

Bit Error Rate Test

Pass Rate (%) 98.7% 99.2% 99.1%

Anti-jamming

Test

Immunity Level

(dB) 75 dB 78 dB 76 dB

Anti-Multipath

Interference

Performance (dB)

80 dB 82 dB 81 dB

Phase noise

immunity (dBc/Hz) -110 dBc/Hz -112 dBc/Hz -111 dBc/Hz

Data Loss

Rate Test

Frequency Shift

Resistance (Hz) 1 kHz 800 Hz 900 Hz

Average Data Loss

Rate (%) 0.8% 0.6% 0.7%

Maximum Data

Loss Rate (%) 2.1% 1.8% 2.0%

Data Loss Pass

Rate (%) 96.2% 97.3% 96.9%

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4.4. ENVIRONMENTAL AND DISTURBANCE TESTING

In the application and practice of electronic communication engineering, the testing

of environmental and interference factors is crucial and significantly affects the

performance and reliability of communication systems. Table 4 shows the results of

the interference immunity test, on a high-speed moving vehicle, the signal interference

strength is -18 dB, the signal-to-noise ratio is 20 dB, and the BER is 0.015%. This

indicates that on mobile vehicles, the communication system can maintain better

performance at higher speeds with high signal quality and low BER. In mountainous

and forested areas, the signal interference strength is -28 dB, the signal-to-noise ratio

is 11 dB, and the BER is 0.05%. This indicates that in complex terrain such as

mountainous areas and forests, the communication system may face higher

interference with slightly poorer signal quality and slightly higher BER. Over the

airplane, the signal interference strength is -12 dB, the signal-to-noise ratio is 22 dB,

and the BER is 0.008%. This indicates that at high altitude and in flight, the

communication system performs well with high signal quality and very low BER. It is

possible to determine the performance of the communication system under different

environmental conditions and to be able to take appropriate measures to cope with

signal interference and improve the stability and reliability of the system.

Table 4. Anti-interference test results

Test Scene Signal Interference

Strength (dB)

Signal-to-noise ratio

(dB) BER (%)

Indoor

environment -20 15 0.02

Outdoor urban

environment -15 18 0.01

Around tall

buildings -25 12 0.03

On high speed

moving vehicles -18 20 15

Open rural areas -30 10 0.04

Inside industrial

plants -22 14 25

Mountain

woodlands -28 11 0.05

Coastal areas -16 19 12

Over airplanes -12 22 8

Inside subway

tunnels -32 8 0.06

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5. CONCLUSION

This paper explores several aspects of digital signal processing oriented electronic

communication engineering applications and practices, performance evaluation in

different communication scenarios, signal-to-noise ratio comparisons, resource

consumption analysis, and system stability and reliability testing. Digital signal

processing performs best in most scenarios, with a slower growth in time complexity,

and especially excels when the number of communication nodes is 1000. The time

complexity of digital signal processing is only 2.5 ms at 0 number of communication

node labels, compared to 4.6 ms for fiber optic communication and 4.9 ms for digital

technology. Digital signal processing not only excels in performance, but also has a

significant advantage in speed and efficiency when dealing with communication tasks.

When the signal-to-noise ratio is as low as -10 dB, digital signal processing shows a

significant performance advantage over fiber optic communication and digitization

techniques. This suggests that digital signal processing is the optimal communications

processing method when operating at low signal-to-noise ratios because of the ability

to demonstrate superior performance under these harsh conditions.

6. DISCUSSION

With advances in digital signal processing technology, communications systems will

be able to provide higher data transmission speeds and greater capacity, enabling

rapid transmission and real-time processing of data-intensive applications such as

high-definition video, virtual reality, and augmented reality. Digital signal processing

will also play a key role in improving the reliability of communication systems by

providing more stable communication connections through digital signal processing

technologies that can better cope with signal interference, noise and other

communication barriers. Future digital signal processors will be more energy efficient

while providing higher performance. This is critical for applications such as mobile

devices, IoT devices and drones that need to operate for long periods of time. As

communication networks expand, security and privacy protection will become critical

issues. Digital signal processing can be used to encrypt, decrypt and identify security

breaches to ensure secure communications.

ABOUT THE AUTHOR

Qinghe Wang was born in Xuzhou，

Jiangsu, P.R. China, in 1980. He received the

Master degree from Jiangsu University of Science and Technology, P.R. China. Now,

he works in Jiangsu College of Tourism. His research interests include education

management, electronic communication engineering, enrollment and employment.

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FUNDING

This research was supported by the 2021 Provincial Education Science Planning

Project: Research on the problems and countermeasures of the implementation of the

comprehensive evaluation enrollment policy in higher vocational colleges (D/

2021/03/23).

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