Radio Access Techniques Research Articles

Overloaded Spread Spectrum OFDMA in Outdoor Environment in the More Interleaving Scenario

The advancement of mobile communication technology is driven by innovations or modifications in the latest Radio Access Techniques to meet user demands and enhance capacity. This paper focuses on improving spectral efficiency and average throughput using an OFDM-based multiple access technique. Specifically, we have chosen Overloaded Spread Spectrum OFDMA for this study. Our research findings indicate that implementing a 24% overload leads to an approximate 33% increase in spectral efficiency. This significant improvement demonstrates the potential of Overloaded Spread Spectrum OFDMA in optimizing the performance of mobile communication systems. By increasing spectral efficiency, we can support a larger number of users and higher data rates, which are crucial for the evolving demands of modern mobile networks. This study highlights the importance of adopting advanced access techniques to sustain the growth and efficiency of mobile communications

Overloaded Spread Spectrum OFDMA in Outdoor Environment in the Low Interleaving Scenario

The development of mobile communication technology starts with creating or modifying a Radio Access Technique (RAT) to meet user needs and increase capacity. This paper focuses on enhancing spectral efficiency and average throughput using an OFDM-based multiple access method, specifically overloaded spread spectrum OFDMA. The study found that with 24% overloading for BPSK modulation, there is approximately a 30% increase in spectral efficiency in outdoor scenarios. There is a significant improvement using higher modulation as well. This improvement highlights the potential of Overloaded Spread Spectrum OFDMA to optimize mobile communication systems, ensuring better resource utilization and system performance to handle the growing demand for data and connectivity effectively

Simulation and Analysis of the Code Domain NOMA with UFMC for 5G Wireless Networks

In fifth generation (5G) wireless networks, radio access techniques and multi-carrier waveforms play a vital role in meeting the diversified demands of ultra-low latency, massive connectivity, and higher throughput. Multi-access schemes used conventionally in 4G system was Orthogonal Multiple Access (OMA) technique. The OMA techniques suffer from inefficient spectrum utilization, high latency, and supports a limited number of users. Next-generation networks, Non-Orthogonal Multiple Access (NOMA), has a great potential, in which multiple users are simultaneously served using the same time, frequency, or code resource increasing the throughput. Code domain-NOMA (CD-NOMA) is the key technique implemented in the system design where multiple users are distinguished based on unique user-specific spreading codes. The NOMA system could significantly benefit from Universal Filtered Multi-Carrier (UFMC) modulation waveform in terms of flexibility, spectral efficiency, compatibility with Multiple Input Multiple Output (MIMO) technique, and relaxed synchronization requirements. The novel integrated system proposed in the paper is CD-NOMA-UFMC with convolutional codes. The major outcome of the paper is that the combination of UFMC air interface modulation technique with CD-NOMA access method can be the most effective way to meet the growing demands of 5G.

Rate Splitting Multiple Access for Next Generation Cognitive Radio Enabled LEO Satellite Networks

Low Earth Orbit (LEO) satellite communication (SatCom) has drawn particular attention recently due to its high data rate services and low round-trip latency. It has low launching and manufacturing costs than Medium Earth Orbit (MEO) and Geostationary Earth Orbit (GEO) satellites. Moreover, LEO SatCom has the potential to provide global coverage with a high-speed data rate and low transmission latency. However, the spectrum scarcity might be one of the challenges in the growth of LEO satellites, impacting severe restrictions on developing ground-space integrated networks. To address this issue, cognitive radio and rate splitting multiple access (RSMA) are the two emerging technologies for high spectral efficiency and massive connectivity. This paper proposes a cognitive radio enabled LEO SatCom using RSMA radio access technique with the coexistence of GEO SatCom network. In particular, this work aims to maximize the sum rate of LEO SatCom by simultaneously optimizing the power budget over different beams, RSMA power allocation for users over each beam, and subcarrier user assignment while restricting the interference temperature to GEO SatCom. The problem of sum rate maximization is formulated as non-convex, where the global optimal solution is challenging to obtain. Thus, an efficient solution can be obtained in three steps: first we employ a successive convex approximation technique to reduce the complexity and make the problem more tractable. Second, for any given resource block user assignment, we adopt KarushKuhnTucker (KKT) conditions to calculate the transmit power over different beams and RSMA power allocation of users over each beam. Third, using the allocated power, we design an efficient algorithm based on the greedy approach for resource block user assignment. For comparison, we propose two suboptimal schemes with fixed power allocation over different beams and random resource block user assignment as the benchmark. Numerical results provided in this work are obtained based on the Monte Carlo simulations, which demonstrate the benefits of the proposed optimization scheme compared to the benchmark schemes.

An intelligent fuzzy-based system for handover decision in 5G-IoT networks considering network slicing and SDN technologies

By enabling 5G technology, IoT networks can improve the performance of connected IoT devices. However, handover, ping-pong effect and load balancing are critical issues because of massive and unplaned deployment of small cells. The handover operation in 5G wireless networks is complicated because there are many radio access techniques and technologies. Therefore, the mobility management is required to provide QoS for various applications. In this paper, we present a fuzzy-based system for handover decision in 5G wireless networks considering different network slicing parameters. We implement two Fuzzy-based Handover Decision Models (FHDM): FHDM1 and FHDM2. We evaluate the proposed models by simulations. For FHDM1, Slice Delay (SD), Slice Bandwidth (SB), and Slice Load (SL) are three input parameters and Handover Decision (HD) is the output parameter. For FHDM2, Slice Reliability (SR) is a new considered parameter, so it has four input parameters and the output parameter is HD the same as FHDM1. We found from simulation results that the considered parameters have different effects on HD. For both models, the HD value increases as SD and SL values increase while HD value is decreasing when SB and SR values increase. The results of the simulation indicate that although FHDM2 is more complex than FHDM1, it performs better HD since considers four input parameters. From the simulation results of FHDM2, when we changed SD value form 10% to 90%, we found that the HD value is increased by 50% when SR is 50% and SL is 90%. This indicates that when a user is connecting with the present slice that has bad QoS, it should handover to another slice with better QoS.

Toward Multi-Service Edge-Intelligence Paradigm: Temporal-Adaptive Prediction for Time-Critical Control over Wireless

Time-critical control applications typically pose stringent connectivity requirements for communication networks. The imperfections associated with the wireless medium such as packet losses, synchronization errors, and varying delays have a detrimental effect on performance of real-time control, often with safety implications. This paper introduces multi-service edge-intelligence as a new paradigm for realizing time-critical control over wireless. It presents the concept of multi-service edge-intelligence which revolves around tight integration of wireless access, edge-computing and machine learning techniques, in order to provide stability guarantees under wireless imperfections. The paper articulates some of the key system design aspects of multi-service edge-intelligence. It also presents a temporal-adaptive prediction technique to cope with dynamically changing wireless environments. It provides performance results in a robotic teleoperation scenario. Finally, it discusses some open research and design challenges for multi-service edge-intelligence.

Design, Challenges and Developments for 5G Massive MIMO Antenna Systems at Sub 6-GHz Band: A Review.

Massive multiple-input multiple-output (mMIMO) is a wireless access technique that has been studied and investigated in response to the worldwide bandwidth demand in the wireless communication sector (MIMO). Massive MIMO, which brings together antennas at the transmitter and receiver to deliver excellent spectral and energy efficiency with comparatively simple processing, is one of the main enabling technologies for the upcoming generation of networks. To actualize diverse applications of the intelligent sensing system, it is essential for the successful deployment of 5G-and beyond-networks to gain a better understanding of the massive MIMO system and address its underlying problems. The recent huge MIMO systems are highlighted in this paper's thorough analysis of the essential enabling technologies needed for sub-6 GHz 5G networks. This article covers most of the critical issues with mMIMO antenna systems including pilot realized gain, isolation, ECC, efficiency, and bandwidth. In this study, two types of massive 5G MIMO antennas are presented. These types are used depending on the applications at sub-6 GHz bands. The first type of massive MIMO antennas is designed for base station applications, whereas the most recent structures of 5G base station antennas that support massive MIMO are introduced. The second type is constructed for smartphone applications, where several compact antennas designed in literature that can support massive MIMO technology are studied and summarized. As a result, mMIMO antennas are considered as good candidates for 5G systems.

A REVIEW OF NEW IMPROVEMENTS IN RESOURCE ALLOCATION PROBLEM OPTIMIZATION IN 5G USING NON-ORTHOGONAL MULTIPLE ACCESS

Because of the arising requirements of emerging networks (Fifth generation and beyond) such as supporting diverse Quality of Services (QoS), low latency, and high spectral efficiency; the previous and traditional generations of communication systems are becoming inappropriate. Furthermore, due to the huge connectivity and ever-growing demands of diverse services and high data rate applications, more effective radio access techniques are required for the purpose of a full-scale implementation of the fifth generation (5G) and beyond wireless systems. Therefore; the researchers are looking for new mechanisms to accomplish these demands, and one of the key techniques been proposed is NOMA due to its capability of spectrum efficiency enhancement. In NOMA-Based systems, the information signals of various users are superimposed at the transmitter side, by utilizing the differences of channel gain to work for different users simultaneously. In this study, recent papers on resource allocation problem based on Power-Doman NOMA (PD-NOMA) in 5G networks were reviewed and the goal (objective function), optimization methods used, and obtained results of each analyzed paper are investigated. In addition, the discussed resource allocation problems were classified into: optimal rate problems and power/energy-efficient problems and the proposed solutions in each of it are analyzed. Finally, this study highlights some of the present and future challenges in this field.

Q2A-NOMA: A Q-Learning-Based QoS-Aware NOMA System Design for Diverse Data Rate Requirements

Wireless use cases in the industrial Internet of Things networks often require guaranteed data rates ranging from a few kilobits per second to a few gigabits per second. Supporting such a requirement in a single radio access technique is difficult, especially when bandwidth is limited. Although nonorthogonal multiple access (NOMA) can improve the system capacity by simultaneously serving multiple devices, its performance suffers from strong device interference. In this article, we propose a Q-learning-based algorithm for handling many-to-many matching problems, such as bandwidth partitioning, device assignment to sub-bands, interference-aware access mode selection [orthogonal multiple access or NOMA], and power allocation to each device. The learning technique maximizes system throughput and spectral efficiency (SE) while maintaining quality-of-service (QoS) for a maximum number of devices. The simulation results show that the proposed technique can significantly increase overall system throughput and SE while meeting heterogeneous QoS criteria.

Call Failure Prediction in IP Multimedia Subsystem (IMS) Networks

An explosion of traffic volume is the main driver behind launching various 5G services. The 5G network will utilize the IP Multimedia Subsystems (IMS) as a core network, same as in 4G networks. Thus, ensuring a high level of survivability and efficient failure management in the IMS is crucial before launching 5G services. We introduce a new methodology based on machine learning to predict the call failures occurring inside the IMS network using the traces for the Session Initiation Protocol (SIP) communication. Predicting that the call will fail enables the operator to prevent the failure by redirecting the call to another radio access technique by initiating the Circuit Switching fallback (CS-fallback) through a 380 SIP error response sent to the handset. The advantage of the model is not limited to call failure prediction, but also to know the root causes behind the failure; more specifically, the multi-factorial root is caused by using machine learning, which cannot be obtained using the traditional method (manual tracking of the traces). We built eight different machine learning models using four different classifiers (decision tree, naive Bayes, K-Nearest Neighbor (KNN), and Support Vector Machine (SVM)) and two different feature selection methods (Filter and Wrapper). Finally, we compare the different models and use the one with the highest prediction accuracy to obtain the root causes beyond the call failures. The results demonstrate that using SVM classifier with Wrapper feature selection method conducts the highest prediction accuracy, reaching 97.5%.

A Novel User Grouping Algorithm for Downlink NOMA

Non-orthogonal multiple access (NOMA) is one of the promising radio access techniques for resource allocation improvement in the (5th) generation of cellular networks. Compared to orthogonal multiple access techniques, NOMA offers extra benefits, including greater spectrum efficiency which is provided through multiplexing users in the transmission power domain while using the same spectrum resources non-orthogonally. Even though NOMA uses Successive Interference Cancellation to repeal the interference among users, user grouping has shown to have a substantial impact on its performance. This performance improvement can appear in different parameters such as system capacity, data rate, or power consumption. In this paper, we propose a novel user grouping scheme for sum-rate maximization which increases the sum rate by approximately 12–25% in comparison with random user grouping and two other authenticated recent works. In addition to being matrix-based and having a polynomial time complexity, the proposed method is also able to cope with users experiencing different channel gains and powers in different sub-bands. Moreover, the proposed scheme is scalable and can be used for any number of users and sub-bands.

A Low-Complexity Codebook Design Scheme for SCMA Systems Over an AWGN Channel

As a promising wireless access technique, sparse code multiple access (SCMA) directly maps the input bits to the transmitted multidimensional codewords according to the SCMA codebook. In general, SCMA codebook optimization and detector simplification are independent of each other. In this article, we propose a simplified SCMA codebook with a separable structure for implementing a low-complexity detector. For codebook design, a separable codebook structure is proposed to simplify the maximization of the minimum Euclidean distance (MED). With this structure, multiple one-dimensional complex codebooks corresponding to one resource element (RE) are determined by maximizing the MED of the superimposed codewords. Then, the entire codebook set is obtained based on a structure indicator matrix and the separable codebook structure. The proposed codebook has a larger MED than obtained by existing codebooks. Benefiting from the separable codebook structure, the signals transmitted over each RE can be independently used to recover the corresponding input bit information. Therefore, we propose a parallel maximum a posteriori (P-MAP) detector consisting of several low-complexity MAP detectors to reduce the complexity of the conventional multiuser message passing (MP) detector in SCMA. At the receiver, each RE is assigned a low-complexity MAP detector. Simulation results show that the proposed codebook outperforms the known optimal codebook over an AWGN channel. Moreover, the run time of the P-MAP detection algorithm is reduced by 99.8% compared to the Log-MPA algorithm. With the proposed codebook design scheme and the P-MAP detector, an SCMA unit can be separated into two independent non-SCMA units, which significantly increases system flexibility.

Energy Efficient and Enhancement Methods For 5G Technology

With the evolution of communication technology, .a corresponding requirement for optimization in energy consumption is also growing. With the..emergence of 5G technology the importance of energy efficiency (EE) for wireless networks has been realized .even more. The major concern is to improve EE without compromising on user experience. So, in this paper, we address various energy issues and provide an analysis of various techniques which will be adopted in. the 5G networks to improve the energy efficiency of the devices. We have focused our attention on the following areas to improve the energy efficiency which include EE improvement using radio access techniques like Simultaneous wireless energy and power transfer, EE improvement by use of Small Cells and Massive MIMO, EE improvement by using relays and D2D communication

Energy Harvesting in Overlay Cognitive NOMA Systems With Hardware Impairments

Combining energy harvesting with cognitive radio and nonorthogonal multiple access (NOMA) techniques will be a notable candidate for improving both energy and spectral efficiency of wireless systems. In this article, we appraise the performance of an overlay cognitive NOMA (OCNOMA) system by employing an energy-harvesting-based spectrum sharing cooperation (SSC) scheme in the presence of hardware impairments (HIs) at the transceiver nodes. Herein, an energy-constrained secondary transmitter node harvests energy from primary transmitter’s radio-frequency signal and utilizes this energy to relay primary information signal as well as to transmit its own information signal using NOMA technique. For this, we investigate two SSC schemes using amplify-and-forward (AF) and decode-and-forward (DF) relaying strategies, named as SSC-AF and SSC-DF schemes. Importantly, we consider the impact of the imperfect successive interference cancellation in NOMA and distortion noises in signal processing due to HIs, which are inevitable in practical systems. Adopting Nakagami- <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</i> fading environments, we derive the expressions of outage probability for primary and secondary networks under both SSC-AF and SSC-DF schemes and, thereby, disclose some pertinent ceiling effects in the system. Furthermore, we evaluate the system throughput and energy efficiency for the considered OCNOMA system. Our results manifest the advantages of the proposed SSC schemes over the benchmark direct primary transmission and orthogonal multiple access schemes.

Guest Editorial: Industrial IoT and Sensor Networks in 5G-and-Beyond Wireless Communication

More data and information is being captured from systems, machines, and devices and made available to industrial information technology (IT) systems. The information is processed on-the-fly, enabling IT-based management systems to generate updated information for real-time control of the manufacturing processes. This data capturing and collection for IT systems is often referred to as the Internet of Things (IoT). When adopted to the industrial requirements, such as robustness, reliability, timeliness, and security, it is often termed as the industrial IoT (IIoT) [A1]. IIoT has attracted the attention of both the industry and academia since it is expected to enhance day-to-day activities, create new business models, products, and services, and as a broad source of research topics and ideas. Meanwhile, it is envisioned that the fifth-generation (5G) networks will be a cornerstone in future wireless industrial connectivity, and currently, there are multitude of ongoing research efforts in their design and optimization. Future industries willembrace use cases with numerous wireless-connected sensors and devices, and judging by the demand, massive machine-type communication and ultra-reliable low-latency communication (URLLC) in the literature and standardization activities, have been identified as two of the three main communication scenarios for 5G. These scenarios demand intelligent, scalable, and robust radio access techniques, network architectures, and deployment options to meet industrial demands [A2]. Therefore, more in-depth research is needed for IIoT and sensor networks in 5G-and-beyond wireless communication systems to address various challenges, including the following. 1)Transmit power control policy should be judiciously designed to improve both the spectrum efficiency and energy efficiency effectively; higher transmit powers can improve reliability but increase the interference and battery consumption. 2)Low-latency communication and computing is one of the significant challenges in 5G-and-beyond IIoT; uploading the device data to the cloud computing centers has high latency and resources waste issues in sensor networks. 3)Addressing privacy and security problems [A3] in the 5G-IIoT is fundamental to the further development and spread of 5G-IIoT. 4)Reliability and latency requirements of URLLC services, requiring less than 1-ms user plane latency and higher than 99.999% reliability, are demanding to meet, especially in time-varying industrial wireless channels. 5)Radio resource allocation, sharing, and isolation with performance guarantees under dynamic traffic conditions are critical issues for emerging IIoT applications requiring real-time support of massive connected devices. 6)5G-and-beyond IIoT networks must satisfy industrial-grade coverage, capacity, time-sensitive networking, and over-the-air time synchronization requirements [A4].

Spectral and energy efficiencies maximization in downlink NOMA systems

Due to the huge connectivity and ever-growing demands of diverse services and high data rate applications, more effective radio access techniques are required for the next generation wireless systems. Non-orthogonal multiple access (NOMA) is a promising candidate which has been recognized as an effective multiple access technique that notably improves the spectral efficiency (SE). In addition to SE, energy efficiency (EE) is also attracting too much interest nowadays due to the limited power of end users (EU) and internet of things (IoT) devices, and the strict environmental concerns related to global carbon dioxide (CO2) emission of communication devices. However, in fact there is a trade-off relationship between SE and EE. In this paper, the SE-EE trade-off relationship in NOMA-based systems is mathematically modeled and analyzed. On the other hand, in order to attain an elastic SE-EE trade-off relationship, the problem is formulated as an optimization problem with an objective of maximizing the EE under the constraint of satisfying a minimum SE demand. Simulation results confirmed the theoretical findings of this study and further asserted the validation of the proposed power allocation scheme which aims to achieve a more flexible trad-off relationship between SE and EE.

Overlay Cognitive IoT-Based Full-Duplex Relaying NOMA Systems With Hardware Imperfections

Energy harvesting with cognitive radio and nonorthogonal multiple access (NOMA) techniques offer a promising solution to enhance the spectral and energy efficiency in Internet of Things (IoT) networks. This article investigates the performance of an overlay cognitive NOMA (OCNOMA) system tailored for IoT applications. Herein, the primary network includes a primary transmitter-receiver pair, whereas the secondary network comprises an energy-constrained full-duplex (FD) relaying-based secondary transmitter (ST) with its intended multiple receivers. Accordingly, ST employs a time-switching (TS)/power-splitting (PS)-based receiver architecture to harvest the energy from the radio-frequency signal of primary transmission and, thereby, uses this energy to relay the primary signal and to transmit its own signals simultaneously using the OCNOMA principle. For this, we propose a cooperative spectrum-sharing transmission (CSST) scheme using the decode-and-forward relaying strategy, while considering the realistic assumptions of FD-based loop self-interference, NOMA-based imperfect successive interference cancelation, and the transceiver hardware impairments in IoT devices. Adopting Nakagami- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${m}$ </tex-math></inline-formula> fading environments, we comprehensively analyze the performance by deriving the expressions of the outage probability for the primary and secondary networks for the FD-based CSST scheme under both TS and PS protocols. Thereby, we disclose some apposite ceiling effects and provide an insight on deciding the value of the OCNOMA power allocation factor for efficacious spectrum-sharing cooperation. We further quantify throughput and energy efficiency for the overall system. Our results demonstrate the performance advantages of the proposed FD CSST scheme over the benchmark schemes and provide useful guidelines for the practical design of cognitive IoT networks.

Joint Multi-User Decoding for Polar-Coded Uplink Non-Orthogonal Multiple Access Systems

Polar-coded non-orthogonal multiple access (NOMA) is a competitive candidate for future wireless physical layer access techniques. The conventional NOMA system employs successive interference cancellation (SIC) for signal decoding. The SIC decoding procedure is optimal only when the code length is sufficiently long. Transmissions with long codes may undergo channel fluctuations. Considering the channel fluctuations, we propose a joint multi-user successive cancellation decoding algorithm for the polar-coded uplink NOMA system. It is shown by simulation results that the proposed joint multi-user decoding algorithm is robust to channel fluctuations.

A Change-Detection-Based Thompson Sampling Framework for Non-Stationary Bandits

We consider a non-stationary two-armed bandit framework and propose a change-detection-based Thompson sampling (TS) algorithm, named TS with change-detection (TS-CD), to keep track of the dynamic environment. The non-stationarity is modeled using a Poisson arrival process, which changes the mean of the rewards on each arrival. The proposed strategy compares the empirical mean of the recent rewards of an arm with the estimate of the mean of the rewards from its history. It detects a change when the empirical mean deviates from the mean estimate by a value larger than a threshold. Then, we characterize the lower bound on the duration of the time-window for which the bandit framework must remain stationary for TS-CD to successfully detect a change when it occurs. Consequently, our results highlight an upper bound on the parameter for the Poisson arrival process, for which the TS-CD achieves asymptotic regret optimality with high probability. Finally, we validate the efficacy of TS-CD by testing it for edge-control of radio access technique (RAT)-selection in a wireless network. Our results show that TS-CD not only outperforms the classical max-power RAT selection strategy but also other actively adaptive and passively adaptive bandit algorithms that are designed for non-stationary environments.

Coverage analysis of indoor users from mm‐wave multi‐RAT small cells deployed along roads

AbstractThe initial deployment of millimeter‐wave (mm‐wave) base stations (BSs), for example, by Verizon and AT&amp;T will be on top of lamp‐posts along the roads of an urban scenario. These deployments will mainly target the outdoor pedestrian users and provide on‐demand ultra‐high data rates. However, as the mm‐wave deployments mature, the operator must necessarily dimension the network by taking into consideration the requirements of the indoor cellular users as well. In this paper, we study the extent of indoor coverage with on‐road BS deployments, so as to enable the network operators with necessary system design and network dimensioning insights. We derive the tier and radio access technique (RAT) selection probabilities of the typical indoor user, and consequently, we characterize its signal to interference and noise ratio (SINR) coverage probability. Based on the density of roads in the city, we prescribe the optimal density of the BSs required to maximize the SINR coverage of the indoor users.