This paper introduces a new analytical framework to evaluate the capacity of intelligent reconfigurable surface (IRS)-aided wireless networks in the presence of a direct link (DL). The obtained analysis is used to characterize the signal-to-noise ratio (SNR) at the user equipment (UE) while using adaptive power and rate transmission. In particular, we consider the channel inversion with a fixed rate, optimum power and rate adaptation, and the truncated channel inversion with a fixed rate. The obtained expressions are derived in a unified closed-form. All the single-hop channel gains are modeled as independent and identically distributed Nakagami-m fading channels. Consequently, the channels’ gains at the receiver become independent and non-identically distributed. The moment generating function (MGF) is used to derive an accurate approximation of the probability density and cumulative distribution functions of the instantaneous SNR, which are used to evaluate the channel capacity at low and high SNRs to quantify the achievable multiplexing gain. The obtained analytical and simulation results indicated that a strong DL may significantly enhance the channel capacity gain obtained using the IRS. In particular scenarios, the capacity improved by about 30% for a large number of IRS elements when the DL Nakagami fading parameter m is increased from 2 to 6.

In non-orthogonal multiple access (NOMA), user pairing, power allocation, and performance evaluation are typically performed while assuming that all users have equal symbol rates. However, such an assumption may significantly limit the design flexibility of NOMA and devalue its potential. Therefore, this paper considers a generalized scenario where the user-paring process may include users with different symbol rates, and thus, the proposed configuration is denoted as multi-rate NOMA (MRNOMA). In MR-NOMA, the relation between the symbol rate and energy is exploited to add a new degree of freedom when assigning power to the paired users. That is, the fact that the symbol energy is proportional to the symbol duration extends the range of power values that can be allocated to the high symbol rate user while satisfying the quality-of-service requirements for all users. Consequently, the number of served users can be increased, or such a feature can be used to increase the link throughput. The obtained results show that with optimal power selection, both the high and low symbol rate users can achieve lower bit error rates (BERs), which in turn increases the system throughput as a result of the improved transmission reliability.

In intelligent reflecting surface (IRS)-assisted communications, the ultimate gain is achieved when the phases of the reflected signals are optimally selected to maximize the signal-to-noise ratio (SNR). However, practical hurdles, particularly the imperfect phase estimation and quantization can reduce the potential gain. Therefore, this work aims at evaluating the impact of applying a quantized phase in the presence of phase estimation errors. Towards this goal, we derive the probability density function (PDF) of the estimated quantized phase, then using the sinusoidal addition theorem (SAT), the PDF of the received signal envelope is derived and used to derive closed-form expressions of the symbol error rate (SER) and outage probability (OP). The obtained analytical and simulation results show that the SER and OP jointly depend on the SNR, phase estimation accuracy, number of IRS elements, and number of quantization levels. The imperfect phase and quantization demonstrated several counterintuitive results. In particular, it is shown that increasing the number of IRS elements or the number of quantization levels may degrade the system performance. Moreover, the results reveal that the impact of phase quantization increases as the phase estimation accuracy decreases. The results also show that the performance is susceptible to phase errors with an even number of reflectors and binary quantization levels.

Physical layer security (PLS) can be adopted for efficient key sharing in secured wireless systems. The random nature of the wireless channel and channel reciprocity (CR) are the main pillars for realizing PLS techniques. However, for applications that involve air-to-air (A2A) transmission, such as unmanned aerial vehicle (UAV) applications, the channel does not generally have sufficient randomness to enable reliable key generation. Therefore, this work proposes a novel system design to mitigate the channel randomness constraint and enable high-rate secret key generation (SKG) process. The proposed system integrates physically unclonable functions (PUFs) and CR principle to securely exchange secret keys between two nodes. Moreover, an adaptive and controllable artificial fading (AF) level with interleaving is used to mitigate the impact of low randomness variations in the wireless channel. The proposed system can operate efficiently even when the channel is nearly flat or time invariant. Consequently, the time required for generating and sharing a key is significantly shorter than conventional techniques. We also propose a novel bit extraction scheme that reduces the number of overhead bits required to share the intermediate keys. The obtained Monte Carlo simulation results show that a key agreement can be reached at the first trial for moderate and high signal-to-noise ratios (SNRs), which is substantially faster than other PLS techniques. Moreover, the results show that inducing AF into static channels reduces the mismatch ratio between the generated secret sequences and degrades the eavesdropper’s capability to predict the secret keys.

This work proposes two algorithms for maximizing the sum-rate and fairness in downlink non-orthogonal multiple-access (DL-NOMA) systems with indoor-outdoor user pairing. Specifically, one of the proposed algorithms is based on the streamlined simplex method (SSM), while the other utilizes the least and most cost method (LMCM). The fairness rate in both cases is optimized using the max-min approach for the indoor device, which is assumed to have a lower channel gain due to its inherently more challenging environment. Various performance metrics such as the achievable data rate, fairness index, and energy-efficiency are analyzed to evaluate the effectiveness of the proposed algorithms relative to different benchmarks such as the Near-Far pairing (NFP) and the random user-pairing (RUP). The results show that the LMCM algorithm incurs lower complexity and offers better data rate and energy-efficiency when compared to the SSM algorithm, the NFP and RUP methods.

Data download and storage over wireless networks is a popular application for various multimedia such as images, audio, and video files. In such applications, the end-user may listen to or watch the downloaded media in real-time, and/or will playback the downloaded file multiple times in the future. Consequently, improving the quality of the stored multimedia will be highly desirable by the end-user, even if the initial real-time version had less quality. Therefore, this work proposes a novel technique to improve the throughput of wireless networks that adopt  nonorthogonal transmission and automatic repeat request (ARQ). Unlike conventional systems, the proposed scheme stores the dropped data packets for further offline processing where some packets can be recovered by applying successive interfer-ence cancellation (SIC) in a retroactive manner. Consequently, the proposed packet repair and recovery (PRR) scheme can improve the reliability of the received data without additional packet retransmission, which may offer a significant throughput gain. To evaluate the effectiveness of the proposed scheme, it is applied to image transmission for transportation systems. The obtained results confirm that a considerable portion of the dropped packets can be successfully recovered and the visual quality of the received image can be improved. In particular scenarios, the obtained results show that the proposed PRR technique managed to reduce the packet drop rate (PDR) from 10^{−1} to 10^{−3}, i.e., 100 fold, which implies that 99% of the packets that were initially dropped were successfully recovered.

This work considers optimizing the IRS elements' selection process to reduce the average BER. In addition to BER reduction, reducing the number of elements reduces the overhead associated with phase information feedback to the IRS panel, and allows serving other users in the network. Moreover, the phase error distribution is derived for the case of LoS communications in closed-form.

A document by Benish Sharfeen . Click on the document to view its contents.

This work considers the problem of joint IRS elements and power allocation for UAV networks in the presence of imperfect phase compensation and energy constraints. The allocation problem is formulated to maximize the network sum-rate with minimum individual rate and energy constraints.

Reconfigurable intelligent surfaces (RISs) is a new technology that can be used to create a virtual line-of-sight (LOS) link when the direct link is blocked. The signal-to-noise ratio (SNR) can be significantly improved by optimizing the reflecting elements’ phases to make the reflected signals add coherently at the receiver. Nevertheless, the RIS cannot control the phase of the direct link if it exists. In such scenarios, the RIS phase can still be controlled such that the direct and reflected signals add coherently, however, the gain obtained by using the RIS might be hindered. Therefore, this paper considers the performance analysis of such scenarios where a novel analytical framework is developed to evaluate the SNR, outage probability and bit error rate (BER). To capture a broad range of fading conditions, the channels are modeled as independent but not identically distributed generalized κ-µ shadowed fading channels. The Laguerre expansion is used to derive the probability density function (PDF) and cumulative distribution function (CDF) of the instantaneous channel fading, which are used to derive the PDF and CDF of the instantaneous SNR. The paper also considers deriving the asymptotic PDF, CDF, moment generating function (MGF) of the SNR, as well as the outage probability and BER. The derived expressions are used to evaluate the system performance in various fading environments such as Rayleigh, One-Sided Gaussian, Nakagami-m , Rician, and Rician-shadowed distributions since they are special cases of the κ-µ shadowed distribution. The obtained analytical results corroborated by Monte Carlo simulation show that a strong direct link can generally eliminate the gain obtained using the RIS. Therefore, the overhead required for the RIS operation becomes a burden on the network and may cause severe throughput degradation. In such scenarios, the RIS involvement should dynamically controlled to avoid unnecessary complexity and throughput reduction.

This work presents a performance analysis on cooperative non-orthogonal multiple accesses (C-NOMA) when assisted with energy harvesting enabled unmanned aerial vehicle (UAV) decode-and-forward (DF) relaying. In particular, two scenarios are considered, an outdoor-indoor one, where the NOMA signal propagates through outdoor-to-indoor, and a conventional outdoor scenario where the channel gains follow a k-u generalized fading model. The objectives of this work is to analyze the downlink performance of this C-NOMA system and derive closed-form expressions for the outage probability (OP), ergodic capacity (EC), throughput and energy efficiency (EE) for the users assuming imperfect successive interference cancellation (SIC). In particular, the OP approach considers the individual users’ rate where it is required to satisfy certain quality of service (QoS) requirements. The results provide insights into the considered performance metrics relative to key parameters such as power allocation, power splitting factor, fading parameters, and residual interference. Extensive simulations results are presented to validate the accuracy of the derived expressions.

Abstract—Non-orthogonal multiplexing (NOM) is a novel superposition coding inspired scheme that has been recently proposed for improving the power, spectrum efficiency and delay of wireless links with packet error rate (PER) constraints. Despite its efficiency, restricting the number of multiplexed packets to two limits the throughput improvement to 100%. Therefore, this work presents a novel NOM design with unlimited number of multiplexed packets by manipulating the repeated transmissions in automatic repeat request (ARQ) to enhance the power and spectrum efficiency by multiplexing new and repeated packets while taking into account the channel conditions and varying the power per packet in different transmissions. The proposed scheme employs an efficient heuristic algorithm to perform the power assignment and multiplexing decisions. Moreover, the complexity of the proposed NOM can be controlled by enforcing a limit on the maximum number of multiplexed packets per transmission, making it suitable for different types of Internet of Things (IoT) nodes with various computational capabilities. The obtained results demonstrate the effectiveness of proposed scheme, which offers up to 200% spectral efficiency improvement at moderate signal to noise ratios (SNRs), and up to 700% at high SNRs. Furthermore, the new scheme can reduce the transmission power consumption by up to 6 dB in the high SNR region.