Spatial Modulation (SM) has been proposed as a multiple-input-multiple-output (MIMO)-based technique to overcome the inter-channel interference experienced in conventional MIMO systems. It has been further shown that SM enhances energy efficiency and reduces the receiver’s complexity. Nevertheless, under high antenna correlation scenarios, the detection performance of the antenna indices degrades significantly. To address this critical concern, in this paper, we propose three autoencoder-based frameworks for spatial modulation. The first scenario, similar to conventional spatial modulation, trains the encoder for data modulation and the decoder for data demodulation as well as antenna index detection. The performance of this framework deteriorates in high antenna correlation scenarios. Therefore, two novel solutions are presented to embed the antenna index into the transmitted signal in order to reduce the receiver’s reliance on the channel conditions. The first framework adds a phase-shift keying-based antenna signature, while the other trains the encoder to learn an appropriate antenna index embedding. Simulation results show that the two enhanced frameworks result in a significantly enhanced performance, compared to conventional spatial modulation, in terms of block error rate and power efficiency under a high correlation setup (about 18 dB and 24 dB gain, respectively, at a Rician factor of 20 dB).

The recent progress of artificial intelligence (AI) opens up new frontiers in the possibility of automating many tasks involved in Telecom networks design, implementation, and deployment. This has been further pushed forward with the evolution of generative artificial intelligence (AI), including the emergence of large language models (LLMs), which is believed to be the cornerstone toward realizing self-governed, interactive AI agents. Motivated by this, in this paper, we aim to adapt the paradigm of LLMs to the Telecom domain. In particular, we fine-tune several LLMs including BERT, distilled BERT, RoBERTa and GPT-2, to the Telecom domain languages, and demonstrate a use case for identifying the 3rd Generation Partnership Project (3GPP) standard working groups. We consider training the selected models on 3GPP technical documents (Tdoc) pertinent to years 2009-2019 and predict the Tdoc categories in years 2020-2023. The results demonstrate that fine-tuning BERT and RoBERTa model achieves 84.6% accuracy, while GPT-2 model achieves 83% in identifying 3GPP working groups. The distilled BERT model with around 50% less parameters achieves similar performance as others. This corroborates that fine-tuning pretrained LLM can effectively identify the categories of Telecom language. The developed framework shows a stepping stone towards realizing intent-driven and self-evolving wireless networks from Telecom languages, and paves the way for the implementation of generative AI in the Telecom domain.

In this paper, we investigate the performance of reconfigurable intelligent surface (RIS)-assisted aerial communications, where a ground base station (GBS) communicates with distant terrestrial and/or aerial users through the assistance of a RIS-equipped unmanned aerial vehicle (RIS-UAV). The GBS uses the non-orthogonal multiple access (NOMA) scheme to transmit its signal, which is directed to the users via the RIS-UAV. First, the end-to-end channel is characterized, by considering the shadowed Rician fading, then the outage probability performance metric is derived for the underlying system model. Through numerical results, we demonstrate the impact of several system parameters on the performance of NOMA users. Specifically, we found that RIS elements need to be carefully allocated among different NOMA users, according to their channel conditions, in order to achieve the needed quality of service.

Jamming attacks, as a form of a denial-of-service attack, significantly degrade the performance of wireless communication systems and can lead to significant overhead in terms of re-transmissions and increased power consumption. In this work, we demonstrate the optimal jamming waveform in internet-of-things (IoT) networks. In particular, we present the analytical bit error rate (BER) of the system under attack by employing two common jamming waveforms: Gaussian noise, and digitally modulated. Then, we validate this analysis with the aid of simulations using the MATLAB WLAN toolbox. Obtained analytical and simulation results, demonstrated system performance degradation under jamming attacks. The simulation results agree with the analytical results in terms of determining the effective jamming waveform. Furthermore, the simulation results depict a 100% PER when the jamming to signal ratio (JSR) is OdB for both QPSK modulated and Gaussian noise waveforms which corroborates with the findings in the literature.

Intelligent reflecting surface (IRS) has emerged as a potential technology to achieve smart wireless communications and high energy efficiency. On the other hand, nonorthogonal multiple access (NOMA)-enabled backscatter communications have shown a great potential in large-scale Internet of Things (IoT) networks. In this article, we consider a downlink IRS-assisted backscatter communication with NOMA. We further consider a two-user scenario with channel disparity from the base station. We first derive the probability density function of the sum of the modulus of reflected channels, where each channel follows the Rayleigh distribution with dissimilar variances. The respective and generalized closed-form outage probability expressions are derived for the considered scenario. Simulation results validate the accuracy of the analytical outage probability expressions. We demonstrate that the far user can achieve a superior performance with the increase of reflecting elements or the reflection coefficients.

This paper investigates different precoding strategies for rate splitting multiple access (RSMA) in the downlink of multi-cell visible light communication (VLC) networks. Since classical Shannon capacity formula does not hold for VLC, we first provide a lower bound on the channel capacity for RSMA in such interfering networks. Then, we formulate a spectral efficiency maximization problem to jointly find the optimal rate-splitting and transmit precoding. Beside that, since cell-edge users suffer from additional inter-cell interference, we propose to design the precoders of different RSMA signals utilizing coordinated beamforming (CB). Subsequently, aiming to improve the performance of the CB design for RSMA, while maintain a reduced complexity, we introduce two enhanced precoding strategies for RSMA. To the best of the authors’ knowledge such a contribution has not been considered before in the open literature. It is shown in the paper that the formulated optimization problem is non-convex and a sub-optimal, yet, a low complexity solution can be obtained efficiently using semi-definite relaxation combined with successive convex approximation. Through analytical results, we illustrate the flexibility and superiority of the proposed precoding strategies for RSMA over conventional coordinated space division multiple access and non-orthogonal multiple access for different scenarios and network loads.

Large intelligent surface (LIS) has recently emerged as a potential enabling technology for 6G networks, offering extended coverage and enhanced energy and spectral efficiency. In this work, motivated by its promising potentials, we investigate the error rate performance of LIS-assisted nonorthogonal multiple access (NOMA) networks. Specifically, we consider a downlink NOMA system, in which data transmission between a base station (BS) and L NOMA users is assisted by an LIS comprising M reflective elements (REs). First, we derive the probability density function (PDF) of the end-to-end wireless fading channels between the BS and NOMA users. Then, by leveraging the obtained results, we derive an approximate expression for the pairwise error probability (PEP) of NOMA users under the assumption of imperfect successive interference cancellation. Furthermore, accurate expressions for the PEP for M = 1 and large M values ( M > 10) are presented in closed-form. To gain further insights into the system performance, an asymptotic expression for PEP in high signal-to-noise ratio regime, asymptotic diversity order, and tight union bound on the bit error rate are provided. Finally, numerical and simulation results are presented to validate the derived mathematical results.

Non-orthogonal multiple access (NOMA)-based cognitive radio (CR) networks have recently emerged as a promising solution to enhance the spectral efficiency and massive connectivity problems. In this paper, we investigate the error rate performance of relay-assisted NOMA with partial relay selection in an underlay cognitive radio network. In this setup, K relays are used to assist in transmission between secondary NOMA users and a secondary base station (SBS), where the relay (R) with the strongest link with the SBS is selected to amplify-and-forward (AF) its received signals to the secondary receivers. We derive an accurate approximation for the pairwise error probability (PEP) of the secondary users with imperfect successive interference cancellation (SIC). Subsequently, the derived PEP expression is utilized to deduce a union bound, which is considered as an upper bound on the bit error rate (BER). We further formulate an optimization problem to calculate the optimum power coefficients that minimize the derived union bound. Numerical and Monte Carlo simulation results are presented to corroborate the derived analytical expressions and give some useful insights into the error rate performance of each user.

The present contribution analyzes the performance of non-orthogonal multiple access (NOMA)-based user cooperation with simultaneous wireless information and power transfer (SWIPT). In particular, we consider a two-user NOMA-based cooperative SWIPT scenario, in which the near user acts as a SWIPT-enabled relay that assists the farthest user. In this context, we derive analytic expressions for the pairwise error probability (PEP) of both users assuming the both amplify-and-forward (AF) and decode-and-forward (DF) relay protocols. The derived expressions are expressed in closed-form and have a tractable algebraic representation which renders them convenient to handle both analytically and numerically. In addition to this, we derive a simple asymptotic closed-form expression for the PEP in the high signal-to-noise ratio (SNR) regime which provide useful insights on the impact of the involved parameters on the overall system performance. Capitalizing on this, we subsequently quantify the maximum achievable diversity order of both users. It is shown that numerical and simulation results corroborate the derived analytic expressions. Furthermore, the offered results provide interesting insights into the error rate performance of each user, which are expected to be useful in future designs and deployments of NOMA based SWIPT systems.

In this paper, we quantify the effect of residual hardware impairments (RHI) on the error rate performance of a relay-based non-orthogonal multiple access (NOMA) system, where the communication between a source node and multiple users is completed via an amplify-and-forward (AF) relay node. In particular, we focus on the pairwise error probability (PEP) analysis and derive an accurate PEP approximation to characterize the performance of NOMA users under Rayleigh fading channels. The derived PEP expression is then exploited to investigate the diversity gain and the union bound on the bit error rate (BER) of the underlying system. Our results demonstrate that the presence of RHI causes an error floor at high signal-to-noise ratio (SNR) values. This error floor yields a detrimental effect on the achievable diversity order of NOMA users, where it is shown that the diversity order of all users converges to zero.

Non-orthogonal multiple access (NOMA) is currently considered as a promising technology for the next-generation wireless networks. In this paper, the error rate performance of NOMA systems is investigated over Nakagami-m fading channels, while considering imperfect successive interference cancellation. In particular, this paper focuses on the pairwise error probability (PEP) analysis, where exact PEP expressions are derived to characterize the performance of all users under different fading conditions. The obtained PEP expressions are then used to derive an exact union bound on the bit error rate (BER). Through the derived PEP expressions, the asymptotic PEP analysis is presented to investigate the maximum achievable diversity gain of NOMA users. Moreover, using the derived BER bound, the power allocation problem for all users in NOMA systems is considered under average power and users BER constraints, which allows realizing the full potential of NOMA. Monte Carlo simulation and numerical results are presented to corroborate the derived analytical expressions and give valuable insights into the error rate performance of each user and the achievable diversity gain.

This paper presents an efficient blind channel estimation technique for orthogonal frequency division multiplexing (OFDM) systems over-time varying channels. New frame structure is proposed, where different modulation schemes are employed to estimate the time-varying channel coefficients. Amplitude shift keying (ASK) and phase shift keying (PSK) modulation schemes are utilized to modulate particular pair of subcarriers over consecutive OFDM symbols, where the ASK and PSK symbols cooperate to enable blind estimation of the channel coefficients. In particular, PSK modulated symbols are employed in the amplitude- coherent detector (ACD) to allow blind detection for the ASK symbols. After that, the detected ASK symbols, with interpolation, are used to estimate the channel coefficients for the full frame. Exact closed-form expression for the symbol error rate (SER) of the ASK symbols is derived and corroborated with Monte Carlo simulations to evaluate the performance of the proposed technique and compare it with the pilot based OFDM system. Analytical and simulation results show that the proposed estimator can provide estimation with accuracy and computational complexity that are comparable to pilot based estimators.

Vehicular ad hoc networks (VANET) are emerging as a prominent form of mobile ad hoc networks (MANETs) and as an effective technology for providing a wide range of safety applications for vehicle passengers. Nowadays, VANETs are of an increasing importance as they enable accessing a large variety of ubiquitous services. Such increase is also associated with a similar increase in vulnerabilities in these inter-vehicular services and communications, and consequently, the number of security attacks and threats. It is of paramount importance to ensure VANETs security as their deployment in the future must not compromise the safety and privacy of their users. The successful defending against such VANETs attacks prerequisite deploying efficient and reliable security solutions and services, and the research in this field is still immature and is continuously and rapidly growing. As such, this paper is devoted to provide a structured and comprehensive overview of the recent research advances on VANETS security services, surveying the state-of-the-art on security threats, vulnerabilities and security services, while focusing on important aspects that are not well-surveyed in the literature such as VANET security assessment tools.