Frequency Resources Research Articles

Uplink resource shared interference mitigation scheme for in-band D2D underlay 5G networks

The benefits of Device-to-Device (D2D) communication often include increased overall system throughput, reduced latency, and increased spectrum efficiency. These advantages usually come from improved spatial reuse of time and frequency resources and the last but not least, the proximity of users engaged into D2D communication. Radio Resource allocation is a critical issue in D2D model and if not dealt with carefully, it can lead to significant interference to both pure cellular and D2D users, thereby proving detrimental to the desired outcomes. This paper presents novel Uplink Resource Shared Interference Mitigation Scheme called URSIMS. URSIMS adopts guard zones, further it implements radio resource allocation algorithm (RRAA) and distance dependent dynamic power control algorithm (DDDPA) with the goal to mitigate interference and achieve increased overall system throughput and spectral efficiency. URSIMS has been compared with other similar state of the art both for static and user mobility based scenarios; it is found that URSIMS responded adequately well and outperformed Random and Greedy schemes in terms of salient performance indicators including overall system throughput, pure cellular user throughput, spectral efficiency and D2D pair throughout. URSIMS did provide sustained higher system throughput, which significantly improved further in case of increased user mobility while compared to Random and Greedy schemes respectively.

Learning to optimize power allocation in cell-free massive MIMO networks with hybrid green energy

In cell-free (CF) massive multiple-input multiple-output (MIMO) networks, many access points (APs) simultaneously serve user equipment (UEs) using the same time and frequency resources. The resource allocation algorithm in such networks needs to handle many calculations within a limited time frame to determine the power allocation from each AP to each UE. Further, the dispersion and large number of APs in CF massive MIMO networks pose challenges in terms of energy supply. As access to the power grid may be limited, renewable energies are often required as a supplement. However, due to the non-deterministic nature of the charging process, the resource allocation algorithm needs to consider the dynamic and uncertain amount of energy available at the APs. In this article, we propose a scalable machine learning algorithmbased on the emerging Learning to Optimize (L2O) paradigm that utilizes neural networks (NNs) for resource allocation in CF massive MIMO networks powered by electrical and renewable energies. Our objective is to minimize energy consumption from the power grid while satisfying the spectral efficiency (SE) constraints of the UEs. Additionally, our algorithm adopts a forward-looking approach and employs a green energy budgeting mechanism to prevent service interruption at green APs during energy shortages. Our algorithm design approach involves formulating the offline version of the problem as a second-order cone program (SOCP). Subsequently, we train an NN using the solutions obtained from solving the online variant of the SOCP. Our results indicated that our L2O-based algorithm can accurately mimic the solutions of the optimization problem with significantly reduced computational complexity.

A Systematic Review on Non-Orthogonal Multiple Access (NOMA) Based on Visible Light Communication for Intelligent Transportation Systems

Non-Orthogonal Multiple Access (NOMA) is a cutting-edge technology that permits several users to use the same frequency resources and transfer data at once. Visible light communication also known as VLC, is an innovative technology that offers access to an unoccupied spectrum, enables fast data transmission speeds, thereby making it a complementary addition to current radio frequency technology. Although VLC has its advantages, it also comes with some downsides. One major issue is the modulation bandwidth of LEDs, which can be quite challenging when creating high speed VLC systems. Non-orthogonal multiple access (NOMA), particularly power-domain NOMA (PD-NOMA), has become a viable multiple access approach, ensuring sufficient bandwidth allocation for VLC systems. This study delves into multiple access techniques in VLC systems, in particular NOMA, and discusses its fundamental principles, key ideas and practical implementations like vehicular communication. It also addresses the associated hurdles, such as ensuring equitable distribution of optical power among users, leveraging MIMO technology, and grappling with LED nonlinearity issues. In summary, we underscore the significance of utilizing NOMA-VLC technology to enhance wireless communication systems and optimize spectral efficiency.

Genetic Algorithm for Mode Selection in Device-to-Device (D2D) Communication for 5G Cellular Networks

The widespread use of smart devices and mobile applications is leading to a massive growth of wireless data traffic. With the rapidly growing of the customers’ data traffic demand, improving the system capacity and increasing the user throughput have become essential concerns for the future fifth-generation (5G) wireless communication network. In a conventional cellular system, devices are not allowed to directly communicate with each other in the licensed cellular spectrum and all communications take place through the base stations (BS) and core network. Device-to-Device (D2D) communication refers to a technology that enables devices to communicate directly with each other, without sending data to the base station and the core network. This technology has the potential to improve system performance, enhance the user experience, increase spectral efficiency, reduce the terminal transmitting power, reduce the burden of the cellular network, and reduce end to end latency. In D2D communication user equipment’s (UEs) are enabled to select among different modes of communication which are defined based on the frequency resource sharing. Dedicated mode where D2D devices directly transmit by using dedicated resources. Reuse mode where D2D devices reuse some resources of the cellular network. Outband mode where D2D communication uses unlicensed spectrum (e.g. the free 2.4 GHz Industrial Scientific and Medical (ISM) band or the 38 GHz millimetre wave band) where cellular communication does not take place. Cellular mode where the D2D communication is relayed via gNode B (gNB) and it is treated as cellular users. In this work, the target was to reach the optimal mode selection policy and genetic algorithm method was used with the objective of maximizing the total fitness function. Optimal mode selection policy was presented and analysed amongst cellular, dedicated, reused and outband mode. In the present study of mode selection issues in D2D enabled networks, genetic algorithm was proposed for the case when the cellular user equipment (UE) moves in the network. Quality of service (QoS) parameters, mobility parameters and Analytic Hierarchy Process (AHP) method were used to define the mode selection algorithm. To evaluate the performance of the proposed genetic algorithm, a study of the convergence of the algorithm and the signal-to-interference plus noise ratio (SINR) was done.

Co‐channel interference cancellation based on BSS for multi‐satellite MIMO communication systems with FFR

SummaryMultiple‐input multiple‐output (MIMO) technology can boost the capacity of conventional satellite communications, and full frequency reuse (FFR) can further improve the capacity by making full use of frequency resources. However, FFR will cause severe co‐channel interference and lead to a degradation of channel capacity. Blind source separation (BSS) algorithm can be used to eliminate co‐channel interference and does not require prior information, which avoids the extra occupation of channel frequency resources. While the multi‐satellite MIMO communication system have delay mixing characteristic, the separation performance will be degraded if the delay is ignored. In this paper, DMBSS algorithm for delay mixing is proposed. Firstly, the DMBSS algorithm utilizes Taylor expansion to achieve dimension expansion of observed signals and so as to transform the delay mixing into instantaneous mixing with extended dimension. Secondly, complex non‐orthogonal joint diagonalization algorithm is used to solve the separation matrix equation of extended observation signals and extended source signals and thus to eliminate the co‐channel interference. Simulation results show that for multi‐satellite MIMO communication scenarios with FFR, the proposed algorithm can effectively improve the performance of co‐channel interference cancellation and reduce the value of BER. Furthermore, the influence of order of Taylor expansion on the separation performance is also analyzed and simulated in this paper to show the cost performance of the proposed algorithm.

Camera trapping and telemetry for detecting and quantifying animal interactions: Not anything goes

Telemetry using Global Positioning Systems (GPS) and camera trapping are two widely used approaches to detect animal interactions involving wildlife. However, while the former follows an individual-based approach, the latter follows a population-based approach, which may lead to different outcomes when describing interaction networks. In this study, we compared the performance of GPS telemetry, regular grid camera trapping (CT-RG), and resource monitoring camera trapping (in which cameras are placed monitoring a valuable resource for animals, such as water or food; CT-RM) in detecting and quantifying animal interactions. We used spatially explicit simulated trajectories of 150 individuals of 3 imaginary species. We simulated 9 different scenarios of resource visiting frequency and spatial resource aggregation in the environment to assess the potential influence of animal behavior and landscape structure. The simulated trajectories were sampled using the three approaches with six different sampling efforts each, and the direct and indirect interactions between the three species were quantified. Additionally, CT-RG and CT-RM were applied in Doñana National Park to evaluate their differences and limitations in field application. In terms of simulation, CT-RM offered the best performance in detecting direct interactions, and GPS achieved good performance when using a high number of fixes per hour. Both CT-RM and GPS also achieved good performance in detecting indirect interactions. CT-RG, on the other hand, missed most direct and indirect interactions, but correctly identified the pairs of species that interacted indirectly at some point. In the field trial, CT-RM and CT-RG detected almost the same number of species pairs interacting indirectly. However, CT-RG missed at least half of the species pairs that interacted directly. The spatial aggregation of the resource favors the performance of GPS over CT-RM, while the opposite occurs when the frequency of animal visits to the resource increases. To summarize, CT-RM is the most reliable method for detecting interactions when resource monitoring is feasible (e.g., small ponds in arid areas). Otherwise, GPS may show better performance, although it may miss direct interactions if a high fix rate is not used. Finally, the use of CT-RG should be limited to identify which species could potentially interact indirectly, but not to quantify these interactions.

Passive reputation method with hybrid optimized deep model for spectrum sensing in cognitive radio network based on blockchain

SummaryThe discovery of malevolent users in cognitive radio networks (CRNs) is done by using blockchain‐based technique. For diagnosing the availability of frequency resources, the spectrum sensing (SS) plays an essential role in CRN. It is critical to enable cognitive radio (CR) technology in wireless communication systems for the next generation. Due to the increasing demand of the users, some bands are overloaded and others become underutilized. The CR applied models for vigorously assigning unlicensed users. The missed detection problem occurs in the conventional spectrum sensing schemes, which hampers the proper utilization of the spectrum. These motivated the development of a newly devised passive reputation method with an optimized deep model for spectrum sensing in CRN‐based blockchain. The sensing spectrum in CRN is designed using the cooperative spectrum sensing algorithm. The spectrum sensing is done with the decision made using AlexNet where the weights of AlexNet are trained with a hybrid optimization algorithm, named Honey Badger Remora Optimization (HBRO) algorithm. Thus, the output attained from the Alexnet_HBRO algorithm is considered. Meanwhile, the data are recorded in the blockchain, and then, the passive reputation is performed, and the determined output is considered. At last, the spectrum sensing is carried out by fusing AlexNet and passive reputation output where weights are optimally generated using the proposed Snake Honey Badger Remora Optimization (SHBRO) algorithm. The proposed SHBRO offered a high detection probability of 1, false alarm probability of 0.003, sensing time of 551.567s, and computation time of 210.102s.

Major clinical events and healthcare resource use among patients with long-chain fatty acid oxidation disorders in the United States: Results from LC-FAOD Odyssey program

Major clinical events (MCEs) related to long-chain fatty acid oxidation disorders (LC-FAOD) in triheptanoin clinical trials include inpatient or emergency room (ER) visits for three major clinical manifestations: rhabdomyolysis, hypoglycemia, and cardiomyopathy. However, outcomes data outside of LC-FAOD clinical trials are limited. The non-interventional cohort LC-FAOD Odyssey study examines data derived from US medical records and patient reported outcomes to quantify LC-FAOD burden according to management strategy including MCE frequency and healthcare resource utilization (HRU).Thirty-four patients were analyzed of which 21 and 29 patients had received triheptanoin and/or medium chain triglycerides (MCT), respectively. 36% experienced MCEs while receiving triheptanoin versus 54% on MCT. Total mean annualized MCE rates on triheptanoin and MCT were 0.1 and 0.7, respectively. Annualized disease-related inpatient and ER events were lower on triheptanoin (0.2, 0.3, respectively) than MCT (1.2, 1.0, respectively). Patients were managed more in an outpatient setting on triheptanoin (8.9 annualized outpatient visits) vs MCT (7.9). Overall, this shows that those with LC-FAOD in the Odyssey program experienced fewer MCEs and less HRU in inpatient and ER settings during triheptanoin-treated periods compared with the MCT-treated periods. The MCE rate was lower after initiation of triheptanoin, consistent with clinical trials.

A model for the formation of frames of fragmented user data packets with non-standardized protocol block headers at the channel level

The continuous and dynamic development of satellite communication systems actualizes the issues of the efficiency of using the frequency and channel resource of communication channels. In the conditions of using packet types of transmissions, fragmentation of user data packets is one of the ways to increase the efficiency of using a channel resource. A wide variety of approaches to the formation of the channel layer and their functional ambiguity in the conditions of fragmentation increase the level of uncertainty in the choice of the protocol stack used to build a communication channel, which in turn creates a prerequisite for a decrease in the quality of the use of the channel resource. In view of this, the task of modeling the procedure for forming frames of fragmented user data packets is relevant, taking into account possible variants of non-standardized protocol block headers at the channel level. Based on the studied non-standardized headers of channel-level protocol blocks, reflecting the features of their formation, to present a model for the formation of frames of fragmented user data packets. This will make it possible to identify the necessary set of informative features, the study of which will make it possible to efficiently and with high probability recognize frames of fragmented packets in a digital data stream with packet switching in channels of satellite communication networks for various purposes. The article considers the procedure for forming frames of fragmented user data packets with non-standardized headers of protocol blocks at the channel level used in data transmission channels with packet switching of satellite communication systems for various purposes. The structural and structural-linguistic models of frames of a fragmented package of user data in conditions of transmission over a satellite communication channel have been developed. The structure of signals with fragmented packets of user data based on a directed graph is presented and investigated. The service level indicators of the fragmented user data package frame formation model were evaluated according to parameters that allow an objective assessment of the effectiveness and validity of the use of fragmentation in data transmission in satellite communication channels. The data obtained using the developed model allows us to qualitatively assess the indicators of the level of service of the data transmission channel with fragmentation of user message packets and reasonably prove the effectiveness of the fragmentation described by the model when it is necessary to split the desired message into parts when it is transmitted over the CCC channel.

Transmission of information on a single carrier frequency in a full-duplex radio line

Telecommunication communication is usually provided in duplex mode, which requires the provision of two carrier frequencies and at least twice the bandwidth of the radio channel in a wireless version (subject to a priori equality of the capacities of information sources at both ends of the radio line). Throughout the development of wireless telecommunications technologies, the issue of the efficiency of using the frequency spectrum allocated for transmitting/receiving messages is acutely relevant, namely, reducing the bandwidth occupied by the message. This task has significant limitations, primarily based on minimizing the distortion of transmitted messages that may occur when artificially limiting the bandwidth. Information compression/compaction methods provide some savings in the width of the frequency spectrum, but a marginal reduction in the occupied frequency band can be achieved when the receiving and transmitting paths of both directions operate at the same carrier frequency. The article provides a brief overview of methods to improve the efficiency of using the frequency resource, provides a computer model and a study of the method of wireless information transmission that allows a full-duplex wireless communication channel to be implemented on a single carrier frequency. The above and investigated computer model of the method based on the use of a circulator made it possible to evaluate the effect of additive noise, the difference in amplitude and phase of the interference signal from the transmitter and a copy of the signal from the radio transmitter in "antiphase" on the number of errors (BER). According to the research results, it can be concluded that in order to reduce the number of errors when using a compensator, it is necessary to ensure an exact match of the interference signal from the transmitter and a copy of the signal from the radio transmitter in "antiphase" in amplitude and the phase difference between these signals is equal to 1800. Since an increase in the amplitude difference starting from 0.001 and the phase deviation from 0.10 from 1800 leads to a significant increase in the number of errors even with large values of the signal-to-noise ratio. In addition, when developing a device based on this method, it is necessary to take into account the difference in the amplitudes of the useful signal and "interference from the transmitter". This parameter specifies additional requirements for the device. The task of compensating for interference from the transmitter is simplified by the fact that the parameters of the transmitting signal and the characteristics of the device elements are known in advance.

Beam Tracking Based on a New State Model for mmWave V2I Communication on 3D Roads

<p>The expansion of 5G and Internet of Things has laid a good foundation for the in-depth research of Internet of vehicles. Low frequency resources are scarce, and Internet of vehicles communication requires extremely high communication rate. Millimeter wave can meet the above two requirements, but its characteristics and the complicated communication conditions of Internet of vehicles make it difficult to combine the two. Overcoming these problems and making beam tracking accurate and steady is a major challenge at present. In this paper, a new extended Kalman filter tracking algorithm is proposed for mmWave V2I scenarios. On the basis of the original algorithm, a threshold prediction update mechanism is added. A new scheme is adopted, which takes position and velocity as tracking variables, and the tracking model is derived for the first time in MIMO 3D scenarios based on this scheme. The model considers the three-dimensional road conditions, including the vehicle deflection motion and the millimeter wave link blocked by large vehicles, which is more suitable for practical application scenarios. The simulation results reveal that the position and velocity tracking scheme is superior to the angle and gain tracking scheme, and the tracking error of the proposed algorithm is lower than that of the algorithms using similar state models. Based on the three-dimensional scene, it considers more realistic situations, and is more consistent with the kinematic characteristics of the vehicle and has more practical significance.</p> <p> </p>

WRIST: Wideband, Real-Time, Spectro-Temporal RF Identification System Using Deep Learning

RF emissions' detection, classification, and spectro-temporal localization are essential not only for understanding, managing, and protecting the radio frequency resources, but also for countering today's security threats such as jammers. Achieving this goal for wideband, real-time operation remains challenging. In this paper, we present WRIST, a Wideband, Real-time, Spectro-Temporal RF Identification system. WRIST can detect, classify, and precisely locate RF emissions in time and frequency using RF samples of 100 MHz spectrum in real-time. The system leverages an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">one-stage object detection</i> Deep Learning framework, and transfer learning to a multi-channel visual-based spectral representation. Towards developing WRIST, we devised an iterative training approach which leverages synthesized and augmented RF data to efficiently build a large dataset with high-quality labels. WRIST achieves over <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$99 \%$</tex-math></inline-formula> class detection accuracy, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$94 \%$</tex-math></inline-formula> emission precision and recall, with less than 0.08 bandwidth and time offset ratios in a large anechoic chamber over-the-air environment. In the extremely congested in-the-wild environment, WRIST still achieves over <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$80 \%$</tex-math></inline-formula> precision and recall. WRIST currently supports five 2.4 GHz technologies (Bluetooth, Lightbridge, Wi-Fi, XPD, and ZigBee) and is easily extendable to others. We are making our curated dataset available to the whole community. It comprises over 10 million labelled RF emissions from off-the-shelf wireless radios spanning the five classes of technologies.

QoT-aware tree selection, routing, modulation, and spectrum assignment for filterless EONs over the C + L-band

Filterless optical networks (FONs) as an economical solution use passive couplers/splitters rather than expensive active filter devices. In this way, after intermediate and destination nodes, lightpaths are dropped and continued, which generates leakage signals in other links and wastes spectrum. Thus, designing efficient resource allocation in FONs by considering the leakage signals and their interfering effects is of utmost importance. On the other hand, a gradual transition from wavelength division multiplexing optical networks to elastic optical networks (EONs) is occurring due to their efficient utilization of spectrum. Furthermore, utilizing the L-band beside the conventional C-band for spectrum assignment offers a wide range of frequency resources. Therefore, in this paper, we propose an integer linear program (ILP) to solve quality of transmission (QoT)-aware tree selection, routing, modulation, and spectrum assignment problems in filterless EONs over the C+L-band. Furthermore, we provide heuristic algorithms to deal with complex large-scale networks. The performance gap of the proposed ILP and heuristic algorithms is evaluated over a small-scale (5-node) network. The results show that the ILP and heuristic algorithms have almost the same performance in terms of spectrum usage and assigned modulation format, and ILP has a slightly higher generalized signal-to-noise-ratio (GSNR) (0.23 dB or 0.8% at optimum launch power). Furthermore, the heuristic algorithms are also examined over a large-scale network (TID region A topology). The results reveal that the GSNR estimation method severely affects the performance in terms of spectrum usage, blocking, and outage. Furthermore, by using the proposed MX5 method, as long as there is a fill margin of approximately 2 dB, there is no outage or blocking over the C+L-band, up to a network throughput of 110 Tbps and conventional C-band transmission with lower throughput (i.e., 40 Tbps). Finally, our extensive numerical results provide a rule of thumb for balancing blocking, outage, spectrum usage, and the number of expensive L-band transponders by selecting the appropriate modulation assignment method.

Fairness aware deep reinforcement learning for grant-free NOMA-IoT networks

Next generation networks have special areas related with the Internet of Things (IoT) to improve the performance of cellular networks in terms of throughput. Grant-free non-orthogonal multiple access (GF-NOMA) seems a feasible solution, letting machine type communication (MTC) devices transmits their packets when they ready to transmit. GF-NOMA increases the spectral efficiency by using the superimposing signals with different power levels over the same time and frequency resources. However, the main drawbacks of GF-NOMA are randomness and the management of power level selection of MTC devices. In 6G-IoT networks, the intelligence should be met to random access. It is time to design new access methods to solve the GF-NOMA issues that should be between the randomness and fully coordinated medium access. Deep-Q-Network (DQN) has become a very hot research topic in recent years that let the MTC devices to make a smart decision in an intelligent way to improve the throughput. Selfishness is an undesirable behavior of DQN for GF-NOMA system where the resources have different cost. In this study, we develop a novel learning framework for power domain GF-NOMA. The goal of our learning framework is to maximize the throughput considering fairness in power consumption which provides long-life to the IoT network. The learning algorithm push the MTC devices to exchange the resources between each other over time. The results show that the proposed method outperform the NOMA scheme with random selection in terms of throughput and increase the fairness index when the DQN with selfish behavior is employed.

Developing Uplink Power Optimization and ARS Selection Algorithm for Multi-ARS Small Cell Communication System

Small Cell (SC) models and unmanned aerial vehicles (UAVs) acting as aerial relay stations (ARSs) are both promising advancements in the development of upcoming wireless networks that contribute significantly to improving the overall service quality. In this work, we rely on the Multi-ARS Cell-Free (CF) model, where a large number of ARS coordinated by the ground base station (GBS) and cooperate to serve a large number of users within the same frequency and time resources, to develop the uplink of a multi-ARS SC system, in which each user is served by only one ARS. The time division duplex (TDD) mechanism is used for communication protocol, and the Minimum Mean Square Error (MMSE) method is implemented to estimate the uplink channel. We derive an closed-form expression for uplink user throughput. In addition, we introduce the ARS selection method based on channel conditions and propose the Bisection algorithm to optimize uplink power. The system performance is evaluated by the cumulative distribution function (CDF) of user throughput according to different parameters, such as changing the number of ARS, the number of users, the number of antennas, and the length of pilot sequences with/without power optimization. The results reveal that the ARS selection method is effectively resolved to reduce complexity and improve the practicality of the proposed system, and the power optimization problem for better throughput is non-optimization.

Frequency Resource Allocation Using Combined Evaluation Function in High Throughput Satellite Communication System

Frequency Resource Allocation Using Combined Evaluation Function in High Throughput Satellite Communication System

QoS-Aware Precoding for Dual-Polarized Downlink Massive MIMO LEO Satellite Communications

Low Earth Orbit (LEO) satellite communications (SATCOM) are important for wireless networks and offer better global wireless access services than higher altitude SATCOM options. SATCOM performance is affected by the number of antennas, which is usually constrained by the satellite space. In this paper, the application of dual-polarized technology is considered to assist LEO SATCOM. Compared with single-polarized antennas, dual-polarized antennas utilize two different polarization orientations to transmit and receive data. This can improve the quality of service (QoS) performance, as it allows for twice the amount of data to be transmitted over the same time–frequency resources. Specifically, we characterize the dual-polarized channel in massive multiple-input multiple-output (MIMO) LEO SATCOM and investigate the precoding design for enhancing the system performance. In particular, a precoding optimization problem is formulated, which aims to jointly optimize the system throughput and the QoS performance. We divide the problem into two stages and develop novel algorithms for each stage to obtain the precoding vectors. The numerical results demonstrate that the dual-polarized technology can improve the system throughput, and the proposed algorithm leads to a higher percentage of users achieving their QoS requirements compared to conventional approaches.

Interference Management Using Distance-based Clustering Method for D2D Communication Underlaying Multicell Cellular Network

Device-to-Device (D2D) communication is a technology candidate to support the next generation of cellular communication networks. D2D has the potential to boost the efficiency of frequency resources and system capacity. Generally, D2D performs in-band underlaying or shares frequency channels with traditional cellular users, which can cause co-channel interference problems between these two types of users. This paper offers a solution through a clustering technique for D2D users (DUEs) to reduce interference among DUEs. Clustering technique is performed on DUEs by allocating different frequency channels in a group, in order to reduce the interference effects experienced. Thus, it is expected that through this proposed method, both D2D and cellular users can experience better signal quality with minimal interference effects. Two systems have been considered i.e., the conventional/baseline system and the system with the proposed clustering method. The simulation results show that the SINR (Signal to Interference plus Noise Ratio) values and throughput for the proposed system compared to the baseline system has increased. The SINR result obtained is 16.8 dB for the baseline system and 17.68 dB for the proposed system, and resulting an improvement of 5.4%. Therefore, applying the proposed clustering method is able to increase acceptability of the desired signals for the observed DUEs. Then, the throughput value also increases by 5%, i.e., from 56.17 to 59 Mbps, which the system with the proposed clustering method provides a better increase in data transmission speed compared to the baseline system.

Heuristic Greedy-Gradient Route Search Method for Finding an Optimal Traffic Distribution in Telecommunication Networks

Rapid growth in the volume of transmitted information has lead to the emergence of new wireless networking technologies with variable heterogeneous topologies. With limited radio frequency resources, optimal routing problems arise, both at the network design stage and during its operation. We propose an algorithm based on a minimum loss intensity (greedy-gradient algorithm) to search for optimal routes of information transmission in telecommunication networks. The relevance of the developed algorithm is determined by its practical use in data-transmitting modeling systems. The proposed algorithm satisfies several requirements, such as the speed of the calculations performed, the fulfillment of the conditions for its convergence, and its independence on the selected loss probability function, as well as on the network topology. The idea of the algorithm is a step-by-step recalculation of metrics based on derivatives of the loss intensity function with simultaneous redistribution of information flows along the routes determined by the Floyd algorithm. The comparative efficiency of the proposed algorithm is demonstrated by computational experiments on various network topologies (up to 100 nodes) with various traffic intensities.

Rainbow link beamforming technology and relevant analysis

In the 5G era, millimeter wave has been mentioned as an important position. Millimeter wave has some problems that cannot be ignored: the free space path loss and atmospheric attenuation. To overcome these problems, millimeter wave systems rely on beamforming to overcome losses. Traditional techniques utilize phase antenna arrays for beamforming, which can cause delays in the time consumption and beam scheduling, and due to limited beams, this technology can only be connected to a limited number of devices, and each transmission occupies the entire bandwidth. This paper introduces a new technology called rainbow link, which is implemented by a new true time delay (TTD) array structure. This technology can achieve the allocation of different subcarriers to a large number of users in the corresponding beamforming direction. Users only need to select appropriate frequency resources. In this work, we calculate the performance of rainbow link with different parameters, and our results show that given 1 GHz bandwidth using 64 element antenna arrays, a rainbow-link cell achieves 1ms latency and 0.6M symbols per second with 0.03 active user rate.