Bit Error Probability Research Articles

Cross-Technology Interference-Aware Rate Adaptation in Time-Triggered Wireless Local Area Networks

The proliferation of IoT using heterogeneous wireless technologies within the unlicensed spectrum has intensified cross-technology interference (CTI) in wireless local area networks (WLANs). As WLANs increasingly adopt time-triggered transmission methods to support real-time services, this interference affects throughput, packet loss, and latency. This paper presents a CTI-aware rate adaptation framework designed to mitigate interference in WLANs without direct coordination with heterogeneous wireless devices. The framework includes a CTI identification model and CTI-aware rate selection algorithms. Leveraging short-time Fourier transform, the identification model captures the time–frequency–power characteristics of CTI signals, enabling the estimation of the average power of various heterogeneous wireless technologies employed by interfering devices. The rate selection algorithms predict CTI occurrence times and adjust the transmission rate accordingly, enhancing the performance of existing explicit and implicit interference mitigation methods. Experimental results demonstrated that the lightweight CTI identification model accurately estimated the average power of each type with an error margin of ±1.414 dBm, achieving this in under 1 ms on the target hardware. Additionally, applying the proposed framework to explicit interference mitigation enhanced goodput by 20.67%, reduced packet error rate by 2.38%, and decreased the probability of packets exceeding 1 ms latency by 0.932% compared to conventional methods.

FaCoCo-RED: A Fast Response Congestion Control Mechanism for Constrained Application Protocol

The rapid growth of the Internet of Things (IoT) has contributed to significant challenges in dealing with congestion within IoT communications due to high packet error rates, latency, and interference in networks. With an emphasis on the Constrained Application Protocol (CoAP), the present study aims to propose the design and development of a novel congestion control mechanism, namely, Fast Response Congestion Control—Random Early Detection, abbreviated as FaCoCo-RED, along with performance analysis and comparison of congestion management efficacy between FaCoCo-RED and Default CoAP Congestion Control (Default CoAP CC) under a Cooja simulator on the Contiki OS platform. The findings from both experiment and performance analysis, which were based on statistical testing, showed that, under medium-scale to large-scale node networks across all traffic scenarios in this study, FaCoCo-RED significantly outperformed Default CoAP CC. The improvement can be seen in such metrics as average throughput, packet loss, response time, settling time, and retransmission timeout values (RTOs). The experimental findings also showed that FaCoCo-RED can perform effectively within the IoT networks, thus potentially enhancing the reliability and scalability of CoAP for large-scale and more complex IoT applications in the future.

CFO and PAPR Analysis for Single‐ and Multistream CIFDMA System

ABSTRACTThe paper investigates the performance of a cyclic interleaved frequency division multiple access (CIFDMA) system proposed in our earlier works. In our present study, the carrier frequency offset (CFO) and the peak‐to‐average power ratio (PAPR) analysis are done for the proposed CIFDMA, supporting single and multiple data stream transmissions. The proposed system is analyzed without employing any compensation technique needed to alleviate the effect of CFO and PAPR. The CIFDMA delivers superior performance over the conventional IFDMA system under low and moderate CFOs. Besides, the bit error ratio (BER) versus signal‐to‐noise ratio (SNR) performance comparisons for constant and random CFOs reveal the dominance of the proposed system over the conventional system for both single and multiple data stream transmissions. The PAPR performance of the proposed system is superior to the orthogonal frequency division multiple access (OFDMA) system. However, the PAPR of the proposed system escalates by an acceptable margin to that of the conventional system, and the deviation in the PAPR value falls within the acceptable range. The simulation results conclude that the proposed CIFDMA system will better replace the conventional IFDMA system for next‐generation communications.

5G Networks Based on Software Defined Network

A software-defined network (SDN) based 5G architecture that utilizes three controllers to improve network performance is proposed in this paper. The controllers are responsible for managing functions related to access mechanism, core connectivity, and network transport. The proposed architecture aims to address solutions for the challenges of traditional 5G networks such as scalability, flexibility, and resource allocation. The paper investigates two networks: 5G without SDN and 5G with SDN. The performance of these networks is evaluated by simulation tests using OMNeT++. The results show a considerable improvement in performance measures such as throughput, packet error rate (PER), and energy consumption. Under favorite test conditions, improvements of 46%, 88% and 94%, in throughput, PER, and energy consumption are achieved. The main finding of the paper is that the proposed SDN-based 5G architecture with multi-controllers is a promising arrangement to overcome the challenges of 5G networks.

Improved Performance of 5G Based Software Defined Networks

With the growth of processed data for wireless networks and the establishment of new applications and services, mobile operators keep searching for solutions to deal with the issues raised by nextgeneration networks (NGN). The fifth generation (5G) mobile networks, for example, should enhance their performance without consuming a lot of energy. For these reasons, software-defined networks (SDN) appear to be the promising technology that will make achieving the architectural agility required for the upcoming 5G mobile networks easier. SDN is a clever solution for providing innovation and enforcing the primary drivers in 5G mobile networks, such as flexibility, dependability, service-oriented management, and cost reduction through the control and management of the 5G core network. In this paper, the integration of SDN and multiple controllers with the 5G core network is investigated to determine how these two technologies can affect mobile IP network performance. An energy model suitable for the proposed network architecture has been developed. A widely used Diamond network is being considered for the core network. Open-Flow controllers were used to improve the routing performance by considering load balancing of IP traffic. According to such a model, reduced energy consumption is experienced with SDN. The addition of an SDN controller results in a 11% reduction in consumed energy. The results also show that the use of SDN and multi-controller with NGN can improve the performance further. Using SDN reduced the average delay of the network by 14%. A great reduction in packet error rate (PER) is also achieved when SDN is used.

RIS–Assisted Propagation Control in CDMA‐FBMC‐OQAM System

ABSTRACTThis framework incorporates the Reconfigurable Intelligent Surface (RIS)–assisted propagation control in Code Division Multiple Access‐Filter Bank MultiCarrier‐Offset Quadrature Amplitude Modulation (CDMA‐FBMC‐OQAM) system. In this system, the modulated signal is reflected by the RIS, which is composed of many tiny passive reflecting elements, and then transmitted through the channel to the receiver. The multiple reflected signals from the RIS are collected at the receiver and then FBMC demodulated and then CDMA despread, which improves the Instantaneous Signal‐to‐Noise‐Ratio (ISNR) of the detected signal. As a result, Bit‐Error‐Probability (BEP) performance is improved.

Performance Improvement by FRFT-OFDM for Visible Light Communication and Positioning Systems

In indoor visible light communication (VLC) and visible light positioning (VLP) systems, the performance of conventional orthogonal frequency-division multiplexing (OFDM) schemes is often compromised due to the nonlinear characteristics and limited modulation bandwidth of light-emitting diodes, the multipath effect in enclosed indoor environments, and the relative positions of transmitters and receivers. This paper proposes an OFDM scheme based on the fractional Fourier transform (FRFT) to address these issues, demonstrating promising results when applied to indoor VLC and VLP systems. The FRFT, a generalization of the conventional Fourier transform (FT) in the fractional domain, captures information in both the time and frequency domains, offering greater flexibility than the FT. In this paper, we first introduce the computation method of the reality-preserving FRFT for an intensity modulation/direct detection VLC system and integrate it with OFDM to optimize system performance. By adopting FRFT-OFDM under the optimal fractional order, we enhance both the bit error ratio (BER) performance and positioning accuracy. Simulation results reveal that the FRFT-OFDM scheme with an optimized fractional order significantly improves the BER and positioning accuracy compared to the FT-OFDM scheme across most receiver positions within the indoor observation plane. For communication, the FRFT-OFDM scheme achieves over 6 dB Eb/N0 gain compared to the FT-OFDM scheme at a BER of 3×10−4 when the receiver is positioned at most locations in the room. For positioning, the FRFT-OFDM scheme enhances positioning accuracy by more than 1 cm relative to the FT-OFDM scheme at most locations in the room. Notably, both systems maintain the same computational complexity and spectral efficiency.

SIC-Free Based Indoor Two-User NOMA-VLCP System

In this letter, an integrated dual-user visible light communication and positioning (VLCP) system based on non-orthogonal multiple access (NOMA) is proposed. The system consists of a single light-emitting diode (LED) and five photodiodes (PD), and the adaptive feedback threshold (AFT) algorithm is used to reduce error propagation (EP) to improve noise immunity. The particle swarm optimization (PSO) algorithm is employed to construct a joint optimization function that optimizes the power allocation factor of the two users and the roll-off coefficient of the square-root-raised-cosine(SRRC) filter. The simulation results demonstrate that, in the given indoor environment, the bit error ratio (BER) of each user in the proposed system is lower than the front error correction (FEC) limit and the average positioning errors of the two users are 4.62 cm and 5.74 cm respectively.

Impact of receiver bandwidth on the performance of nonlinear volterra equalizer in IM/DD systems

Nonlinear electrical equalization is an effective means to compensate for nonlinear waveform distortions in short-haul intensity-modulation (IM)/direct-detection (DD) optical transmission systems. Nonlinear distortions contain broader spectral components than the original signal. Thus, a wide receiver bandwidth and high sampling rate are beneficial to effective compensation of nonlinear distortions. However, this leads to poor signal-to-noise ratio at the receiver. In this paper, we investigate the impact of receiver bandwidth on the performance of 2nd-order nonlinear Volterra equalizer in IM/DD transmission systems. Through the computer simulation and the experimental verification performed with 4-ary pulse amplitude modulation signals, we show that an optimum receiver bandwidth for bit-error ratio performance increases with the amount of nonlinear distortions in IM/DD systems. We also show that the sampling rate should also be increased to avoid the aliasing of the nonlinear distortion components. The cost of the receiver increased by the wider receiver bandwidth and higher sampling rate could be offset in part by the non-integer fractionally sampled nonlinear Volterra equalizer.

Simultaneous generation of dual 16-QAM-modulated millimeter-wave signals enabled by precoding-based optical I/Q modulation and single photodetector detection

Integration of quadrature-amplitude-modulation (QAM) modulation and millimeter-wave (mm-wave) technology ensures a concise enhancement of transmission capacity and peak data rates in radio-over-fiber (RoF) systems. Nevertheless, with the continuous development of new-generation mobile applications, higher demands on access flexibility have also been formulated. We propose a novel, to the best of our knowledge, dual 16-QAM-modulated mm-wave signal generation scheme for the simultaneous generation and transmission of two independent 16-QAM signals with different carrier frequencies, enhancing the channel capacity, spectrum efficiency, and access flexibility of the RoF systems. In our proposed scheme, the generation of the optical dual 16-QAM-modulated mm-wave signals is implemented by a precoding-based optical in-phase/quadrature (I/Q) modulator operating at optical carrier suppression (OCS) mode, and their detection is implemented by a single photodetector (PD). At the transmitter side, two independent driving QAM vector radio-frequency (RF) signals with precoding, generated via digital signal process (DSP), are fed into two parallel Mach–Zehnder modulators (MZMs) of an I/Q modulator to implement OCS modulation. The I/Q modulator generates optical carriers carrying both information from different QAM signals simultaneously. After square-law detection in a single PD, we generate the desired dual 16-QAM-modulated mm-wave signals with photonic frequency-doubling and recover the original 16-QAM signals without information distortion. Based on our proposed scheme, we experimentally demonstrate the simultaneous generation and transmission of 2-Gbaud dual 16-QAM-modulated mm-wave signals with carrier frequencies of 26 GHz and 40 GHz, respectively. After transmission over 10-km single-mode fiber (SMF) link and 1.2-m wireless link, the dual 16-QAM signals can be successfully separated and demodulated by a common DSP. Bit-error ratios (BERs) of both recovered 16-QAM signals can reach the hard-decision forward-error-correction (HD-FEC) threshold of 3.8×10−3. Compared with the existing schemes, our scheme only requires one-half of the driving frequency to generate dual 16-QAM-modulated mm-wave signals with the same carrier frequency. The result indicates that our proposed scheme can lower bandwidth requirements for optoelectronics devices, along with implementing better spectral efficiency and receiver sensitivity, which is more applicable to the demands for increased system capacity and multi-frequency access flexibility in future systems.

Scalability Analysis of LoRa and Sigfox in Congested Environment and Calculation of Optimum Number of Nodes.

Low-power wide area network (LPWAN) technologies as part of IoT are gaining a lot of attention as they provide affordable communication over large areas. LoRa and Sigfox as part of LPWAN have emerged as highly effective and promising non-3GPP unlicensed band IoT technologies while challenging the supremacy of cellular technologies for machine-to-machine-(M2M)-based use cases. This paper presents the design goals of LoRa and Sigfox while throwing light on their suitability in congested environments. A practical traffic generator of both LoRa and Sigfox is introduced and further interpolated for understanding simultaneous operation of 100 to 10,000 such nodes in close vicinity while establishing deep understanding on effects of collision, re-transmissions, and link behaviour. Previous work in this field have overlooked simultaneous deployment, collision issues, effects of re-transmission, and propagation profile while arriving at a number of successful receptions. This work uses packet error rate (PER) and delivery ratio, which are correct metrics to calculate successful transmissions. The obtained results show that a maximum of 100 LoRa and 200 Sigfox nodes can be deployed in a fixed transmission use case over an area of up to 1 km. As part of the future scope, solutions have been suggested to increase the effectiveness of LoRa and Sigfox networks.

Error rates of optically pre-amplified PPM wireless systems with coding and arbitrary optical filter response

We present novel results for the uncoded and coded bit-error probability (BEP) of optically pre-amplified pulse-position modulation (PPM) wireless systems. For uncoded systems, a novel analytic method for the evaluation of the BEP is derived. The method takes into account the non-ideal optical filter response and utilizes a finite Karhunen–Loève series expansion to calculate the BEP. Using the proposed approach, it is possible to accurately evaluate the PPM BEP for arbitrarily shaped filters where the well-established χ2 method only provides approximate results. Considering a Lorentzian filter response, the discrepancy between the two methods amounts to 0.5 dB in a variety of filter bandwidths and PPM modulation orders. The Lorentzian filter response was chosen as an illustrative practical example whose series can be calculated analytically. The proposed method is also valid for any type of optical filter for which the Karhunen–Loève series expansion can be calculated analytically or numerically. Due to the finite number of terms that are required irrespective of the signal energy level, the proposed method can also be applied without loss of accuracy to assess the system performance under the effects of turbulence and adverse weather conditions. For coded systems with Lorentzian filters, Monte-Carlo simulations are utilized to evaluate the BEP performance of the 5G LDPC codes, and it is demonstrated that they impart an energy gain up to 3.3 dB for 4–PPM and 2.3 dB for 16–PPM at a target BEP of 10−5. The optimal code rates are also discussed for several combinations of the optical filter bandwidth and PPM modulation order and it is shown that in almost all of the cases the optimal code rate is 11/13. Moreover, the sum-product and min-sum decoders perform within 0.1 dB from each other for the best code rates, which points towards the utilization of the min-sum decoder in all settings, since its operation does not require knowledge of the filter parameters. Finally, the comparison between the coded systems with Lorentzian and ideal passband filters exhibits the same 0.5 dB discrepancy that was observed for uncoded systems.

Game-Based Intelligent Jamming Strategy without Prior Information in Wireless Communications

Traditional jamming technologies have become less effective with the development of anti-jamming technologies, especially with the appearance of intelligent transmitters, which can adaptively adjust their transmission strategies. To deal with intelligent transmitters, in this paper, a game-based intelligent jamming scheme is proposed. Considering that the intelligent transmitter has multiple transmission strategy sets whose prior probabilities are unknown to the jammer, we first model the interaction between the transmitter and the jammer as a dynamic game with incomplete information. Then the perfect Bayesian equilibrium is derived based on assumptions of some prior information. For more practical applications when no prior information about the transmitter is available at the jammer, a Q-learning-based method is proposed to find an intelligent jamming strategy by exploiting the sensing results of the wireless communications. The design of the jammer’s reward function is guided by the game utility and the reward is calculated based on the Acknowledgement/Negative Acknowledgement feedback of the receiver. Simulation results show that the proposed scheme has only 0.5% loss in jamming utility compared to that of the perfect Bayesian equilibrium strategy. Compared to existing jamming schemes, a higher packet error rate can be achieved by the proposed scheme by consuming less jamming power.

Knowledge hierarchy-based dynamic multi-objective optimization method for AUV path planning in cooperative search missions

This study focuses on path planning for Autonomous Underwater Vehicles (AUVs) in underwater cooperative search missions. The complexities of the ocean environment, the uncertainty of target movements, and limited communication capabilities render underwater cooperative search missions dynamic multi-objective optimization challenges. Studies focusing on communication-constrained search strategies still lack reliable metrics for assessing underwater communication quality and do not consider communication dead zones. Addressing these deficiencies, this paper introduces a novel communication optimization strategy utilizing packet error rate as a metric for assessing communication efficacy, complemented by a potential field-based method for navigating out of communication dead zones. To tackle the inherently dynamic nature of cooperative search missions for mobile underwater targets, we propose a dynamic multi-objective optimization algorithm that employs a knowledge hierarchy strategy. This method enhances the NSGA-II algorithm's efficiency by extracting effective gene segments from historical Pareto solution set and generating a new initial population through recombination, hierarchy, and prediction. Distinct from other advanced dynamic multi-objective optimization approaches that are limited to theoretical problems, our approach is directly applicable to practical scenarios. The effectiveness and practicality of the proposed method are validated through a series of simulation experiments considering the impact of underwater acoustic communication. These results demonstrate that this research is not only innovative in theory but also holds significant engineering value and practical prospects in real-world applications.

ANALIZA STATYSTYK SIECI KOMPUTEROWYCH W CELU IDENTYFIKACJI PRZEPŁYWÓW INFORMACJI ZAKŁÓCAJĄCYCH STABILNOŚĆ W WOJSKOWYCH SIECIACH LOKALNYCH

The increasing complexity and scope of military computer networks necessitate robust methods to ensure network stability and security. This study presents a comprehensive analysis of computer network statistics in military local networks to develop a method for detecting information flows that disrupt stability. By leveraging advanced statistical techniques and machine learning algorithms, this research aims to enhance the cybersecurity posture of military local networks globally. Military networks are vital for communication, data exchange, and operational coordination. However, the dynamic nature of network traffic and the persistent threat of cyberattacks pose significant challenges to maintaining network stability. Traditional monitoring techniques often fail to meet the unique requirements of military networks, which demand high levels of security and rapid response capabilities. This study employs a multi-faceted approach to detect anomalies in network traffic, utilizing statistical methods such as Z-score analysis, Principal Component Analysis (PCA), and Autoregressive Integrated Moving Average (ARIMA) models. Machine learning techniques, including Support Vector Machines (SVM), Random Forests, Neural Networks, K-means clustering, and Reinforcement Learning, are also applied to identify patterns indicative of stability-disrupting information flows. The integration of statistical and machine learning methods forms a hybrid model that enhances anomaly detection, providing a robust framework for network security. The research problem is formulated as follows: does data collection include comprehensive network traffic data from various segments of military local area networks, including packet flows, transmission rates, and error rates over a specified period? Statistical analysis identifies patterns in the network traffic, which are then used to train machine learning models to classify normal and abnormal traffic. The research hypothesis states that machine learning models achieve high accuracy in detecting stability-disrupting information flows, with a precision rate exceeding 90%. The models identified several instances of stability-disrupting events, correlating these with known security incidents to validate the effectiveness of the detection method. This study underscores the importance of continuous monitoring and analysis of network statistics to ensure stability and security. The proposed method can be integrated with existing network monitoring and intrusion detection systems, providing a comprehensive approach to network security. Future research can build on these findings to develop more sophisticated models and explore additional factors influencing network stability, including the incorporation of advanced machine learning techniques, such as deep learning, and the exploration of other network metrics, like latency and packet loss. This comprehensive approach aims to enhance the security and operational reliability of military local networks.

Chaos-driven seven-core optical transmission scheme based on DNA full information chained analog-transcription

This paper proposes a chaos-driven seven-core optical transmission scheme based on DNA full information chained analog-transcription. Unlike traditional deoxyribonucleic acid (DNA) coded encryption schemes in the bit dimension, this scheme uses chaotic sequences to generate perturbed bit streams corresponding to the initial bit stream. These two sets of bit streams are encoded from a set of DNA double-stranded sequences, which are then intertwined into a single-stranded DNA containing all the information through the full-information class transcription algorithm proposed in this paper. Finally, the DNA decoding process is driven by a set of sequences derived from another chaotic model to transform the DNA sequence containing all information back into a bit sequence for subsequent transmission. Additional chaotic sequences interfere with the subcarriers, symbols, and constellation angles. Moreover, to maintain spectral efficiency, hiding the key in the frame header allows for the dynamic simultaneous transmission of signal and key. The transmission of encrypted 16 quadrature amplitude modulation-orthogonal chirp division multiplexing (16QAM-OCDM) signals is experimentally demonstrated at a net bit rate of 51.72 Gb/s over 2 km weakly coupled seven-core fiber. At the receiving end, the correct key decoder is able to accurately recover the data, while the bit error ratio (BER) at the illegal receiving end is 0.5. Finally, quantitative experiments validate the receiver-side decryption algorithm, showing that the proposed encryption scheme achieves a large key space of 10397. The key can be fully decoded when the optical power is above -20dBm. This scheme significantly enhances the security and flexibility of the communication system, making it a promising candidate for future optical communication physical layer encryption.

Simultaneous transmission of multi-format signals in the mid-infrared over free space

Mid-infrared (MIR) light within the 3–5 μm spectrum offers distinct advantages over the 1.5 μm band, particularly in adverse atmospheric conditions, rendering it a favorable option for free-space optical (FSO) communication. The transmission capacity within the 3–5 μm band is relatively low due to the immature state of its devices. In this study, we demonstrate multi-format signals FSO transmission with a total of 40 Gbps capacity in the 3 μm band, utilizing our developed MIR transmitter and receiver modules. These modules facilitate wavelength conversion between the 1.5 μm and 3 μm bands through the utilization of difference-frequency generation (DFG) effect. The MIR transmitter effectively produces three MIR signals: On-Off Keying (OOK), Binary Phase Shift Keying (BPSK), and Quadrature Phase Shift Keying (QPSK) optical signals. The generated MIR power is 7.8 dBm, covering a wavelength range from 3.5864 to 3.5885 μm. The MIR receiver regenerates the three format signals with a power of −29.6 dBm. Relevant results of regenerated signal demodulation have been collected in detail, including bit error ratio (BER), constellation diagram, and eye diagram. The required powers for the 10 Gbps OOK, BPSK, and QPSK are −37.82, −40.24, and −39.4 dBm at BER of 1 × 10−6. It is expected to further push the data capacity to the terabit-per-second level by adding more 1.5 μm band laser sources and using wider-bandwidth chirped nonlinear crystals.

Design and Implementation of Transparent Cross‐Polarization Interference Compensation in a Wideband Dual‐Polarization Satellite Receiver

ABSTRACTIn this paper, simultaneous transmission on two orthogonal antenna polarizations in a polarization division multiplexing (PDM) fashion is studied for wideband satellite communication links using dual‐polarization satellite receivers for the purpose of doubling the data rate. In order to mitigate the cross‐polarization interference (XPI), a new digital blind and transparent XPI compensation method is proposed, coined as XPI correlation learning estimation and adaptive reduction (XPI‐CLEAR). The received signal‐to‐noise‐and‐interference ratio (SNIR) and packet‐error rate (PER) performance with this non‐data‐aided and non‐decision‐directed method is assessed in a comprehensively modelled XPI channel with effects such as depolarization due to atmospheric conditions, imperfect cross‐polarization discrimination (XPD) of the antennas at the transmitter and the receiver, memory effects due to frequency selectivity of the XPD, and differential frequency offset (DFO) between the two channels. The application of the XPI‐CLEAR method presents considerable energy efficiency improvements for all the studied XPI channel effects, and is particularly beneficial for higher order modulation. A low‐complexity hardware implementation with symbol rates up to 500 MBaud validates the XPI‐CLEAR method as a practical solution to increase the data rates of the satellite air interface and to achieve the doubling of the throughput of the satellite link by the use of PDM.

Experimental demonstration of quantum encryption in phase space with displacement operator in coherent optical communications

We provide experimental validation of quantum encryption in phase space using displacement operators in coherent states (DOCS) in a conventional coherent optical communication system. The proposed encryption technique is based on displacing the information symbols in the phase space using random phases and amplitudes to achieve encryption randomly and provide security at the physical layer. We also introduce a dual polarization encryption approach where we use two different and random DOCS to encrypt the X and Y polarizations separately. The experimental results show that only authorized users can decrypt the signal correctly, and any mismatch in the displacement operator coefficients, amplitudes, or phases will lead to a bit error ratio (BER) of approximately 50%. We also compare the performance of the system with and without encryption over 80 km of standard-single mode fiber (SSMF) transmission to assess the added penalty of such encryption. The achieved net bit rates are 224, 448, and 560 Gb/s for QPSK, 16QAM, and 32QAM modulation formats, respectively. The experimental results showcase the efficacy of the DOCS encryption technique in resisting various decryption attempts, demonstrating its effectiveness in ensuring the security and confidentiality of transmitted data in a real-world transmission scenario.

RTTV-TCP: Adaptive congestion control algorithm based on RTT variations for mmWave networks

Internet applications such as video gaming virtual/ augmented reality necessitate efficient fifth-generation (5G) millimeter-wave (mmWave) cellular networks. The Transmission Control Protocol (TCP) is an essential protocol for network connectivity. However, TCP faces challenges in efficiently utilizing the available bandwidth of 5G mmWave cellular networks while maintaining low latency, mainly due to constraints like Non-Line of Sight (NLoS) conditions. This paper introduces Round-Trip-Time Variations-TCP (RTTV-TCP), enhancing TCP performance in 5G mmWave cellular networks. Simulation scenarios for a 5G mmWave cellular network have been conducted to evaluate RTTV-TCP’s performance, comparing it to legacy TCP variants such as NewReno, HighSpeed, CUBIC, Bottleneck Bandwidth and Round-trip propagation time (BBR), FB-TCP (Fuzzy Based-TCP). The results demonstrate that RTTV-TCP achieves higher average throughput than these TCP variants while maintaining the same level of delay in 5G mmWave cellular networks. RTTV-TCP outperforms NewReno and CUBIC by a very significant margin, demonstrating a 208% improvement compared to HighSpeed and a 6% increase compared to BBR protocol in the worst Packet Error Rate (PER) scenario and when the buffer size matches the Bandwidth Delay Product (BDP).