Modeling and Performance Analysis of DSSS Techniques in 5G

Wireless Systems

Saif Shaikh, Raj Dusane and P. S. Varade

SCTR’s Pune Institute of Computer Technology, (E&TC Department), Pune, Maharashtra, India

Keywords: FDMA, TDMA, CDMA, DSSS, FHSS, PN Sequence, Additive White Gaussian Noise (AWGN).

Abstract: In modern wireless communication systems, the Direct Sequence Spread Spectrum (DSSS) technique plays

a pivotal role in improving signal robustness and resistance to interference. DSSS is a type of spread

spectrum modulation technique where the bandwidth of the transmitted signal is significantly greater than

that of the original message. The expansion of the bandwidth is achieved through spreading the signal with

a pseudo-random noise (PN) sequence, which is essential for both spreading and de-spreading processes.

The maximal length PN sequence (m-sequence) is widely used due to its optimal properties for spread

spectrum communication. In the context of 5G wireless systems, DSSS can provide enhanced spectral

efficiency, secure communication, and robustness against interference. The performance of DSSS in 5G

systems is closely tied to the quality of the PN sequence and its ability to mitigate interference, noise, and

multipath fading. This study focuses on modeling the DSSS technique and evaluating its performance in 5G

networks, with particular emphasis on signal robustness, interference management, and spectral efficiency.

The results will demonstrate the potential benefits of integrating DSSS into next-generation 5G wireless

systems.

1 INTRODUCTION

The development of 5G technology marks a

significant leap in communication systems, offering

faster data rates, lower latency, and the ability to

connect a vast number of devices. However, these

advancements bring new challenges, particularly in

managing interference, ensuring signal robustness,

and optimizing spectral efficiency. In dense 5G

environments, where signals are prone to

interference and fading, techniques like Direct

Sequence Spread Spectrum (DSSS) can play a

critical role.

DSSS spreads the transmitted signal across a

wider bandwidth using a pseudo-random noise

sequence, enhancing security and resilience against

interference. This approach makes the signal more

robust, reducing the impact of noise and jamming. In

5G networks, where efficient spectrum usage and

interference management are key, DSSS offers a

promising solution for improving overall

performance.

This study aims to model and analyze the

performance of DSSS techniques in 5G wireless

systems, focusing on critical metrics such as signal

robustness, spectral efficiency, and interference

management. By exploring the integration of DSSS

in 5G, this research seeks to highlight its potential to

enhance the reliability and efficiency of next-

generation wireless networks..

2 MULTIPLE ACCESS

TECHNIQUE

Multiple access technique where many users or local

stations can uses the communication channel at the

same period of time or nearly so despite the fact

originate from different locations. A multiple access

method is a definition of how the radio spectrum is

split into channels and how the channels are

allocated to the many users of the system. Since

there are different users transmitted over the same

channel, a method must be established so that

individual users will not disrupt one another.

There are three basic types of multiple access

technique

Shaikh, S., Dusane, R. and Varade, P. S.

Modeling and Performance Analysis of DSSS Techniques in 5G Wireless Systems.

DOI: 10.5220/0013586400004664

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 3rd International Conference on Futuristic Technology (INCOFT 2025) - Volume 2, pages 49-56

ISBN: 978-989-758-763-4

A. Multiple Access via Frequency Division

(FDMA)

B. Multiple Access with Time Division

(TDMA)

C. Multiple Access over Spread Spectrum

(SS-MA)

• Direct sequence spread spectrum

(DSSS)

• Frequency-hopped spread spectrum

(FHSS)

2.1 Multiple Access via Frequency

Division (FDMA)

FDMA assigns each user a distinct frequency band

or channel for communication. These separate

frequency bands are made available to users seeking

communication services, ensuring that no other user

can use the same frequency band during its assigned

time. As a result, when an FDMA channel is not in

use, it becomes idle and cannot be used by other

users to expand or share capacity. This exclusivity

enables for continuous communication, but it might

result in inefficiencies in spectrum utilization when

channels are empty. To successfully tune in and

receive broadcast signals, the receiver just has to

know the allotted frequency.

Figure 1: FDMA System Blocks.

2.2 Multiple Access with Time Division

(TDMA)

TDMA enables multiple users to share the same

frequency bandwidth, but only for specific time

slots. Each user transmits during their assigned time,

which prevents overlap. If transmissions do overlap,

it causes co-channel interference. Precise clock

synchronization is essential to ensure that each user

transmits in their designated time slot, maintaining

effective communication and minimizing

interference.

Figure 2: TDMA System Blocks.

2.3 Spread Spectrum Multiple Access

Spectrum uses signals with a transmission

bandwidth that exceeds the minimum needed RF

bandwidth. A pseudo-noise (PN) sequence converts

a narrowband signal into a wideband signal,

increasing immunity to multipath interference.

Although SSMA is not particularly bandwidth-

efficient for a single user, it does allow numerous

users to share the same spread spectrum bandwidth

without interfering. This feature makes spread

spectrum systems especially efficient in multi-user

scenarios, which appeals to wireless system

designers. Spread spectrum multiple access

techniques are classified into two types: frequency

hopping (FH-MA) and direct sequence (DS-MA),

often known as code division (CDMA).

2.4 Direct Sequence Spread Spectrum

Direct Sequence Spread Spectrum involves a

transmitter and receiver system as illustrated in

Figure (3). In the transmitter, the baseband data

signal m(t) m(t) m(t) is spread using a pseudo-noise

(PN) sequence c(t), resulting in a spread signal s(t).

Figure 3: DSSS System Blocks

INCOFT 2025 - International Conference on Futuristic Technology

This spread signal is modulated using binary

shift keying (BPSK), resulting sending of signal x(t),

which is a binary direct sequence phase shift keying

signal (DS/BPSK).

Figure 4: DSSS Signal with PN Code.

At the receiver, the transmitted signal is

demodulated using a coherent detector and then

multiplied by the same PN code c(t). This

multiplication effectively removes the PN code from

the received signal, restoring the original data signal

d(t). It’s noteworthy that the spreading operation

performed in the transmitter is mirrored by the de-

spreading operation in the receiver, allowing for

accurate recovery of the original signal.

3 PERFORMANCE EVALUATION

PARAMETERS OF DSSS IN 5G

Direct Sequence Spread Spectrum (DSSS) in 5G

wireless systems, performance evaluation is based

on several critical parameters. Bit Error Rate

measures the accuracy of data transmission,

indicating how often bits are incorrectly received.

Signal-to-Noise Ratio reflects the clarity of the

signal, comparing signal power to background noise.

Processing gain shows how effectively the spread

spectrum improves resilience against interference.

Spectral efficiency evaluates the efficient use of

bandwidth, while latency and throughput determine

speed and system capacity.

Additionally, delay spread is a crucial parameter,

representing the time difference between the arrival

of the direct signal and reflected signals, which

affects signal clarity. Jamming resistance, another

vital factor, evaluates DSSS's ability to maintain

communication in the presence of intentional

interference, which we will discuss further in the

paper. These parameters together help assess DSSS's

reliability, robustness, and performance in 5G

environments.

3.1 BER and SNR

Bit-Error-Rate is a critical performance metric for

evaluating Direct-Sequence-Spectrum systems in 5G

wireless networks, which require high reliability and

low latency for applications like autonomous

vehicles and remote healthcare. The BER is defined

as the ratio of incorrectly received bits (Ne ) to total

transmitted bits (Nt)

𝐵𝐸𝑅

𝑁𝑒

𝑁𝑡

)

DSSS enhances signal robustness by spreading

data over a wider bandwidth, which significantly

reduces the BER. The processing gain (G) of a

DSSS system can be expressed as:

𝐺

𝐵𝑠

𝐵

𝑑

)

Where Bs is the bandwidth of the spread signal

and Bd is the bandwidth of the original data signal.

Higher processing gain leads to improved SNR,

which in turn lowers the BER. The relationship

between SNR (ɣ) and BER for Binary Phase Shift

Keying (BPSK) is approximated by:

𝐵𝐸𝑅

.𝑒𝑟𝑓𝑐





)

where erfc( ɣ) is the complementary error

function. As SNR increases, BER decreases,

demonstrating DSSS's effectiveness in challenging

environments.

SNR is defined as the ratio of received signal

power (Ps) to noise power (Pn):



𝑃𝑠

𝑃

𝑛

)

In DSSS, processing gain enhances effective

SNR by combating interference and multipath

fading, essential for reliable 5G communication

among numerous connected devices. The use of

pseudo-noise (PN) sequences allows DSSS to handle

co-channel interference effectively, maintaining low

BER.

Modeling and Performance Analysis of DSSS Techniques in 5G Wireless Systems

Figure 5: BER Vs. SNR Various 5G Waveforms Testing

The graph depicts the Signal-to-Noise Ratio

(SNR) against Bit Error (BER) for various 5G

waveforms such as OFDM, FBMC, SC-FDMA,

UFMC, 16-QAM, and 64-QAM.

Curves are quite close, showing a gradual

decrease in BER with increasing SNR, dropping to

below 10⁻⁴ around 12

-15

dB SNR.

3.2 Delay Spread

Delay spread is a critical parameter in 5G wireless

communications, particularly in systems using

Direct Sequence Spread Spectrum (DSSS)

techniques. It refers to the time dispersion of

multipath signals as they arrive at the receiver,

caused by reflections and scattering from various

obstacles in the environment. In urban

environments, for example, delay spreads can range

from 50 to 200 nanoseconds (ns), while in more

complex environments, such as dense urban areas, it

may exceed 1 microsecond (µs). In 5G, where high

data rates (up to 10 Gbps) and low latency (as low as

1 ms) are essential for applications like autonomous

vehicles and remote healthcare, significant delay

spread can lead to inter-symbol interference (ISI),

where overlapping delayed signals interfere with one

another, resulting in data errors.

𝑇𝑟𝑚𝑠



∑|

ℎ



𝑡𝑖

|

2.𝑡𝑖𝑇𝑚𝑒𝑎𝑛2





∑

|ℎ



𝑡𝑖







)

To quantify delay spread, the Root Mean Square

(RMS) delay spread can be calculated using the

following equation:

Where:

• Trms is the RMS delay spread.

• h(ti) is the impulse response of the channel

at time ti

• Tmean is the mean delay, calculated as

Tmean

• N is the number of multipath

components

Figure 6: Power Delay Spread Profiles of 5G Tech

The graph shows Exponential Power Delay

Spread Profiles for a 5G system, comparing how the

signal's relative power decreases over time (in

nanoseconds) for various decay factors (0.05, 0.1,

and 0.15) and number of paths (5, 10, and 15).

• Higher decay factors lead to faster drops in

power.

• Increasing the number of paths (multipath

components) also accelerates the power decay.

For example, a decay factor of 0.05 with 5 paths

shows a slower decline in signal strength, while a

decay factor of 0.15 with 15 paths results in rapid

decay within the first 20 ns. This highlights how the

environment affects signal fading in 5G networks.

3.3 Jamming

Because 5G networks are made to Communication

designed for many low-data IoT devices,

Eenhanced-mobile-broadband, and Highly reliable

low-delay communication, jamming becomes an

even more serious problem. To evaluate the effect of

jammers on 5G, performance metrics like Packet

Send Ratio (PSR) and Packet Delivery Ratio (PDR)

are crucial.

INCOFT 2025 - International Conference on Futuristic Technology

3.3.1. Packet Send Ratio (PSR) in 5G:

In 5G, PSR remains an important metric to evaluate

how successfully data packets are transmitted by the

sender. As 5G supports high-bandwidth and low-

latency applications, a jammer that targets the high-

frequency bands (such as millimeter waves) or

causes congestion in lower-frequency bands can

drastically reduce PSR. The massive device

connectivity in 5G networks also increases the

likelihood of interference, where a jammer can

reduce PSR by causing collisions and overwhelming

the network with noise, especially in dense

environments with numerous IOT devices.

3.3.2. Packet Delivery Ratio (PDR) in 5G:

With 5G's promise of reliable communication,

especially in mission-critical applications like

autonomous vehicles, smart factories, or healthcare,

a jammer’s effect on PDR can have serious

consequences. A low PDR indicates interference at

the receiver, preventing devices from receiving

packets reliably.

In 5G, where latency-sensitive applications

require near-instant data delivery, a jammer can

exploit vulnerabilities in beam forming, massive

MIMO, or the use of small cells to create localized

disruptions. A reduced PDR in 5G could lead to

service outages, delay-sensitive failures, or even

safety risks in critical applications.

3.3.3. Packet Delivery Ratio (PDR) in 5G:

5G networks, with their multi-access edge

computing (MEC) and network slicing technologies,

can detect jammers more efficiently using real-time

monitoring of PSR, PDR, signal strength, and carrier

sensing time. These parameters can be used to

identify abnormal distributions caused by jammers,

particularly through advanced techniques like

machine learning that can identify and adapt to new

jammer strategies.

4 LITERATURE RIVIEW

Table 1: Study of 5G based on DSSS Systems.

Ref. No work System Design/Technology Used Comparative Parameters

Adrian et

al. (Adrian

et al.

2004) –

IEEE

Journal

"BER of No

coherent

Unbalanced

DQPSK in DSSS"

• Conventional Demodulator:

Needs coherence.

• Non-Coherent Demodulator:

Tolerates cross-talk.

• Focus: BER model.

• Finding: Minimal BER impact

from noise.

• No coherent Demodulation: ~5dB loss

at low SNR.

• BER: Affected by I/Q cross-correlation.

• Simulation: Matches theory at high

SNR.

Behrouz et

al.(

Behrouz et

al. 2020) -

IEEE 3rd

5GWF

"CP-DSSS for

5G"

• CPDSSS: Coexists with OFDM.

• Comparison: CPDSSS vs.

OFDM.

• Channel Model: Similar to CP-

SCM.

• Symbol Rate: ≤ bandwidth.

• Operates at low SINR (-10 dB).

• Low data rates (<100 kbps).

• PAPR < 4 db.

• Similar to CP-SCM

• Reduces interference.

• Secondary channel for 5G NR...

Hongling

et al.

(Li,

Pei et al.

2010)–

ICITIS

"DSSS with

Jamming"

• Focus: DSSS with jamming.

• Conclusion: BER affected by

SNR, JSR, PN sequence, and

frequency/phase.\

• Key Point: Longer PN sequence

doesn't enhance performance

with optimal jamming.

• DSSS with single-tone jamming.

• BER depends on SNR, JSR, PN

sequence, and frequency/phase

difference.

• Synchronization disruption is a key

tactic in jamming.

• O

timal JSR limits BER increase.

Xianbin et

al.

(Xianbin et

al. 2011)-

ICEMI

"Fast Acquisition

in LEO DSSS"

• Focus: High dynamic spread

spectrum signals (>100 KHz

Doppler shifts) in LEO

satellites.

• Method: Fast acquisition using

FFT.

• DSSS in LEO faces 100 KHz Doppler

shifts.

• FFT-based method for fast signal

acquisition.

• Implemented with FPGA+DSP for

faster speed and detection...

Harshali et "Compressed

• Focus: DSSS transmission with

com

ression.

• SNR Improvement – +6 dB at low

SNR.

Modeling and Performance Analysis of DSSS Techniques in 5G Wireless Systems

al.(

Harshali et

al 2015) -

ICSTM

DSSS

Transmission"

• Signals: Text, binary, speech,

and images.

• Techniques: Huffman

compression and Discrete

Cosine Transform.

• BER Reduction – 0.001 at 10 db.

• Compression Ratio – 3:1 with Huffman

Ahmed et

al.( Ahmed

et al.,

2017) -

IEEE

"ML Time Delay

in 5G MIMO

DSSS"

• Focus: Two ML TDE methods

for multi-carrier DSSS in 5G

MIMO.

• First TDE: EM method with

initialization.

• Second TDE: IS method

without initialization.

• 0 Gbps data rate

• 50% faster with IS method

• Handles 1 µs delay spread

• 20% better delay accuracy

Faouzi et

al.( Faouzi

et al.,

2016) -

ICREMT

"ML Time Delay

in 5G DSSS

MIMO"

• Focus: TDE from SC/MC DSSS

in 5G with multiple antennas.

• Results: EM for large

observations; IS for short

records.

• CRLB: 1.2 ms accuracy.

• EM TDE: Effective for 1000+ samples.

• IS TDE: Best for <100 samples.

• Robustness: >95% accuracy with

correlations.

Zhang et al

(Zhang et

al. 2012) -

ICCECT

"PN Sequence

Estimation for

Weak DSSS"

• Focus: PN sequence period

estimation in low SNR DSSS

signals.

• Method: Wavelet

decomposition and power

ectrum re

rocessin

• BER: 10⁻⁶ in AWGN

• Bandwidth Expansion: 10-20x

• Multipath Tolerance: 50%

Sanjay et

al. (Sanjay

et al, 2017)

CMS

"Spread

Spectrum

Modulation

Performance"

• Focus: Wireless communication

advancements.

• Solution: Spread spectrum

communication.

• Results: DSSS-BPSK offers

etter BER.

• Anti-Jamming: 30dB

• Security: Low Probability of Intercept

Mohamme

d et al.(

Mohamme

d et al.,

2023 )

Alexandria

Engineerin

g Journal

"6G Technology:

Requirements and

Challenges"

• Improvements: Enhances 5G

limitations.

• Applications: Supports 3D

communications and XR/VR.

• Requirements: Ultra-low

latency and extreme speed

• Latency: Ultra-low (sub-millisecond)

• Data Rate: 100x increase (compared to

5G)

• Connection Density: 10⁶ devices/km²

Astha et al.

(Astha et

al, 2013)

CAC2S

"Spread Spectrum

Performance

Analysis"

• Analyzes wireless

communication performance.

• Increases bandwidth and

jamming resistance.

• Originated in military; now used

for analog and digital data.

• Processing Gain (PG): 10 dB to 60 dB.

• Bandwidth Expansion: Up to 100 xs.

Adam et

al. (Adam

et al., 2000

)- The

University

of Texas at

Austin

"DS Spread

Spectrum"

• Purpose: Ensures secure radar

and communications.

• Advantages: Security, selective

addressing, and interference

rejection.

• Limitations: Trade-offs

required; not all benefits can be

used at once.

• Signal Power Density: Lower than

narrowband, measured in watts per

hertz (W/Hz).

• Traffic Growth: 55% per year

Azita et

al.( Azita

et al, 2020)

- IJECE

"eDSSS for SINR

Mitigation in

LTE-Wi-Fi"

• Issue: LTE data demand

increased Wi-Fi offloading.

• Challenge: Wi-Fi interference at

2.4 GHz with LTE.

• 4.69% SINR improvement for MUEs.

• 17.94% SINR improvement for WUEs.

• Optimized chip rate coefficient (α =

0.2).

INCOFT 2025 - International Conference on Futuristic Technology

• Solution: Enhanced DSSS.

• Result: α = 0.2 improved SINR

by 4.69% for Mobile Users,

17.94% for Wi-Fi Users.

• Reduced co-channel interference.

Dayana et

al (Dayana

et al.,

2019)-

IJECE

"Modified IOTA

for 5G Cognitive

Radio"

• Issue: Spectrum scarcity.

• Solution: Cognitive radio (CR)

for spectrum sensing.

• Focus: Spectrum sensing in

multi-carrier systems.

• Result: UFMC-based CR

outperforms OFDM in

efficienc

and data rates.

• Data Rate: 20% improvement.

• Spectral Efficiency: 15% better.

• Complexity: 10% lower.

• SNR: 5 dB improvement.

• Latency: 30% faster.

Taeho et

al. (Taeho

et al, 2013)

- JCSE

"Security in DSSS

Signals"

• Challenge: Security issues from

the broadcast nature of

communication.

• Countermeasure: DSSS

technology to combat jamming.

• Enhancements: Keyless DSSS

and watermarked DSSS for

better security

• Innovation: Ada

tive DSSS

• Jamming Resistance: Requires 100x

stronger signal to jam.

• Interference Rejection: 20 dB

improvement in SNR.

• Privacy: 256-chip spread sequence for

privacy.

• Usage: Adopted in IEEE 802.11 (Wi-

Fi) and IEEE 802.15.4.

5 CONCLUSIONS

The study of Direct Sequence Spread Spectrum

(DSSS) techniques in 5G wireless systems

demonstrates their critical role in enhancing signal

robustness and managing interference. DSSS

effectively expands the bandwidth of transmitted

signals using pseudo-random noise (PN) sequences,

providing improved spectral efficiency and secure

communication. The analysis highlights key

performance metrics, such as Bit-Error Rate and

Signal-to-Noise Ratio.

For instance, the processing gain (G) of DSSS

can be expressed as the ratio of the bandwidth of the

spread signal (Bs) to that of the original data signal

(Bd). In practical scenarios, if Bs=20MHz and

Bd=1 the processing gain GGG would be 20, leading

to a significant reduction in the BER, potentially

achieving values as low as 10−6 under optimal

conditions. The SNR is critical for the performance

of DSSS, with an ideal scenario yielding an SNR of

γ=15dB, which translates to a BER of approximately

1.3×10−5 for Binary Phase Shift Keying (BPSK)

modulation.

Additionally, the examination of delay spread

emphasizes the importance of addressing inter-

symbol interference for maintaining data integrity in

high-speed applications. For example, in urban

environments, the Root Mean Square (RMS) delay

spread can be as high as 200ns , while in more

complex environments, it may exceed 1μs,

potentially causing severe ISI.

Overall, the integration of DSSS into next-

generation 5G networks presents significant

potential for improving communication reliability,

efficiency, and security, making it a valuable

technique for meeting the demands of modern

wireless communications.

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