Priority-based subcarrier allocation algorithm for maximal network connectivity in 5G networks

Multiuser orthogonal frequency division multiplexing (OFDM) is a very promising multiple access technique to efficiently utilize limited RF bandwidth and transmit power in wideband transmission over multipath fading channels. When a wideband spectrum is shared by multiple users in multiuser OFDM-based systems, different users may experience different fading conditions at all subcarriers. Each user is assigned a subset of all subcarriers by some allocation algorithm. Thus, multiuser diversity can be achieved by adaptively adjusting subcarrier, bit, and power allocation depending on channel status among users at different locations (Wong et al., 1999a). In (Wong et al., 1999a), Wong applies a Lagrangian optimization technique and an iterative algorithm to solve the subcarrier, bit and power allocation problem. The suboptimal scheme for the NP-hard joint optimization problem is decoupled into two steps while it has a high computational complexity. A sub-optimal algorithm has been proposed to solve a related problem (Wong et al., 1999b). In (Wong et al., 1999b), Wong presents a real-time subcarrier allocation (SA) algorithm. It is a two-phase algorithm, including the constructive initial assignment (CIA) and the subcarrier swapping steps. The initial subcarrier allocation algorithm needs to pre-determine the numbers of subcarriers for each user before the allocation process starts. The performance of the SAbased algorithm will be compared in the simulation. In (Kim et al., 2006), Kim shows that the allocation problem in (Wong et al., 1999a) can be transformed into an integer programming (IP) problem. The branch-and-bound algorithm (Wolsey, 1998) can be employed to find the optimal solution of the allocation problem which has exponential computational complexity in the worse cases. We utilize the approach to obtain the optimal solution as the performance bound for comparison. Evolutionary algorithms (EA) are used to solve extremely complex search and optimization problems which are difficult to solve through simple methods. EAs are intended to provide a better solution, as it is based on the natural theory of evolution. Evolutionary algorithm (EA)-based schemes have been applied to solve subcarrier, bit, and power allocation problems (Wang et al., 2005) (Reddy et al., 2007) (Reddy & Phora, 2007) (Pao & Chen, 2008). In general, chromosomes can be designed with binary, integer, or real representation. The chromosome lengths are related to the number of subcarriers. Each element in the chromosome is a subcarrier allocated to a user. In this research, a subset of subcarriers can be assigned to one user depending upon the availability of subcarriers at a particular time

In this paper, the problem of subcarrier allocation, and power allocation is addressed in an OFDM-based two-tier femto-cell network comprising of a conventional macro-cell and multiple femto-cells. The macro-cell users near the femto-cell causes significant interference to the femto-cell users as well gets interfered by the femto-cell transmissions. We present a subcarrier and power allocation method in underlay femto-cell network while keeping the total interference to macro-cell users under acceptable levels. We maximize the multiple femto-cell users throughput by jointly allocating subcarriers to users within a femto-cell, and also power allocation, under the constraints of cross-tier interference between macro-cell and multiple femto-cells as well as interference among femto-cells. Then, based on this subcarrier and power allocation the performance of the two-tier network is analysed with capacity as the performance metric.

The development and establishment of mobile communication technologies has necessitated assessments of possible risks to human health from exposures to radio-frequency electromagnetic fields (RF EMF). A number of expert committees have concluded that there is no evidence for such risks as long as exposures are at or below levels that do not allow tissue heating. These assessments have been based primarily on studies investigating frequencies up to 6 GHz including frequencies similar to those used by two of three major bands of fifth generation (more accurately 5G New Radio or 5G NR) of mobile communication. Bioeffects studies in so-called high-band at 25–39 GHz are particularly sparse. Future assessments relevant for these frequencies will need to rely on still unperformed studies. Due to few available studies at 5G NR “high band” frequencies, and questions raised by some existing studies, a recent review recommended a wide range of RF biostudies be done at 5G NR “high band” frequencies. It is of importance that such studies be done using the best possible science. Here we suggest factors to consider when performing future studies in this area. The present focus is on laboratory studies to clarify biological effects of radiofrequency (RF) energy at 5G “high band” frequencies and, more generally at millimeter wave (mm-wave) frequencies (30-300 GHz) which will be increasingly used by communications technologies in the future. Similar comments would apply to epidemiology and exposure assessment studies, but those are not the focus of the present Perspective.

SummaryFor the first time, 3GPP considered in Release‐17 the introduction of mobile satellite service (MSS) frequency bands for 3GPP user equipment (UE) direct connectivity with satellites and had to consider the coexistence in adjacent bands with terrestrial networks (TNs). This paper will further explain the most challenging and the main surprising outcomes of this work, which opened new market opportunities for both terrestrial and nonterrestrial stakeholders. 5G New Radio nonterrestrial networks (NTNs) for satellite communications are representing a major breakthrough in the history of telecommunication for the capability of reuniting two different types of services, that is, terrestrial and nonterrestrial, by reusing the same waveform and potentially the same type of terminal. One of the major conclusions of the 5G NR NTN 3GPP work in Release‐17 was that NTN UE could reuse the current requirements of the TN UE. For this reason, the same terminal can connect to both TNs and to nonterrestrial satellite constellations. Consequently, the market is not fragmented and therefore there will be a real opportunity for both terrestrial and satellite operators to increase the coverage and the quality of the service all over the world. This is one of the most important breakthroughs that 3GPP Release‐17 work was able to justify because it clearly shows that satellite connectivity using 5G NR technology is not only for dedicated satellite 5G NR UE with a higher power class. On the other hand, the 3GPP work also shows that the satellite connectivity does not require a dedicated satellite waveform, because 5G NR waveform based on CP‐OFDM (for downlink) and DFT‐s‐OFDM (for uplink) is sufficient. Another important finding is that TN can coexist with NTN on adjacent channels with relaxed ACIR requirements for the tested simulation scenarios. In fact, the satellite 5G NR requirements are lower when compared with terrestrial base station (BS) requirements from previous 3GPP releases. The satellite ecosystem tremendously changed after these findings, and both satellite and terrestrial stakeholders now see a potential market opportunity.

In this work, we investigate the uplink resource allocation problem for virtualized wireless networks (VWNs) supported by multi-carrier non-orthogonal multiple access (MC-NOMA) and present a sensitivity analysis of such a system to imperfect successive interference cancellation (SIC) and various system parameters. The proposed algorithm for power and sub-carrier allocation is derived from the non-convex optimization minimizing power subject to rate and sub-carrier reservations, for which an optimal solution is NP-hard. To develop an efficient solution, we decompose the optimization into separate power and sub-carrier allocation problems and propose an iterative algorithm based on successive convex approximation and complementary geometric programming. Simulation results demonstrate that compared to orthogonal multiple access, for imperfect SIC with residual interference even up to 10%, the proposed algorithm for MC-NOMA can offer significant improvement in spectrum and power efficiency.

The performance of the multiprocessor system and time-sharing system rely upon CPU scheduling algorithm. Some of the well known efficient CPU scheduling algorithms are Round Robin scheduling (RR), Shortest job first(SJF), Preemptive version of SJF(SRTF), First Come First Serve (FCFS) etc. As of now, the Round Robin scheduling algorithm is considered as the efficient process scheduling algorithm among all the existing CPU scheduling algorithms. However, in RR the shortest one have to wait for a longer time and in SRTF longer process behaves as a suspended process as short tasks keep on executing. This paper proposes a new scheduling process algorithm ESRR (Efficient Shortest Remaining Time Round Robin) that consolidate two of the preemptive version of existing scheduling algorithms namely RR and SRTF. ESRR reduces total waiting time and turn around time in compare to RR and reduces the waiting time of the shorter process and it also provides a longer process to execute faster than SRTF.

CPU scheduling is the basis of multi-programmed operating systems. The scheduler is accountable for multiplexing processes on the CPU. By switching the CPU among processes, the operating system results in the computer more prolific. Various CPU scheduling algorithms exist for a multi-programmed operating system like First Come First Served (FCFS), Shortest Job First (SJF), Shortest Remaining Time Next (SRTN) and Round Robin (RR) scheduling algorithm. This paper has threefold objective. Firstly, it throws light on a new-fangled CPU scheduling algorithm called MIN-MAX whichbehaves as both preemptive and non-preemptive algorithm basis on the burst time. Secondly, it would helps to understand how MIN-MAXalgorithm improves the CPU efficiency in multi programming operating system and also trims down the starvation problem amongprocesses. Thirdly, it focuses on the comparative study of the existing algorithms on basis of various scheduling parameters with the proposed algorithm MIN-MAX.

Lightweight blockchain assisted secure routing of swarm UAS networking

Temporal dependence in workloads creates peak congestion that can make service unavailable and reduce system performance. To improve system performability under conditions of temporal dependence, a server should quickly process bursts of requests that may need large service demands. In this paper, we propose and evaluateASIdE, an Autocorrelation-based SIze Estimation, that selectively delays requests which contribute to the workload temporal dependence. ASIdE implicitly approximates the shortest job first (SJF) scheduling policy but without any prior knowledge of job service times. Extensive experiments show that (1) ASIdE achieves good service time estimates from the temporal dependence structure of the workload to implicitly approximate the behavior of SJF; and (2) ASIdE successfully counteracts peak congestion in the workload and improves system performability under a wide variety of settings. Specifically, we show that system capacity under ASIdE is largely increased compared to the first-come first-served (FCFS) scheduling policy and is highly-competitive with SJF.

This paper investigates the adaptive subcarrier and bit allocation algorithm for OFDMA systems. To minimize overall transmit power, we propose a novel adaptive subcarrier and bit allocation algorithm based on channel state information, Moreover, the block-wise method is considered based on channel variation for adaptive subcarrier and bit allocation. It is shown that a near optimal solution is obtained by the proposed algorithm which has low complexity compared to that of other conventional algorithms. Also, it is shown that the block-wise method significantly reduces the complexity and the feedback or side information though has a slight transmit power increase.

Guest editorial IJSCN special issue on 3GPP NTN standards for future satellite communications

The smart city relies on smart management systems to protect the environment and improve the quality of life of citizens. This paper presents some related use cases and lists their various benefits. In addition, given the implementation of the current systems, specific requirements are presented as challenges to improve the actual delivery. To achieve this goal, this paper examines the role and potential of adding 5G New Radio (5G NR) technologies to smart city implementations. 5G NR is a new radio interface fully developed from the most basic level to support a wide variety of deployments and services. Therefore, an overview of 5G technology is provided here, along with a roadmap for the various releases to describe the 5G evolution path. Next, a discussion is conducted on the key services and features of 5G that are capable of supporting the improvement required in smart city development.

In the future, communication networks such as fifth-generation new radio (5G NR) and sixth-generation (6G) will require large data rates and capacities. As a result, mmWave and terahertz (THz) bands are being employed to meet these demands. Unfortunately, these high-frequency bands are susceptible to high path loss, necessitating the deployment of small cells. This, in turn, calls for the installation of a massive number of base stations to cover the whole area. The sheer number of cells and users in such a setup can lead to interruptions in calls when users switch cells, a process known as handover (HO). This has a negative effect on the quality of service (QoS) and the quality of experience (QoE). Therefore, this survey focuses on exploring and comparing artificial intelligence (AI)-based intelligent HO solutions that can optimize HO in 5G NR and 6G networks.

Multi-user orthogonal frequency division multiplexing (OFDM) with adaptive sub-carrier and bit allocation are considered in this paper. Assuming having the knowledge of the instantaneous users' channel gains, three typical dynamic sub-carrier and bit allocation algorithms are analyzed and compared. All the algorithms' goal are to minimize the total transmit power with the user data rate constraint. Here, an improvement method is proposed for Zhang algorithm. Finally, performance comparisons between adaptive schemes and static ones are given. The results prove that adaptive algorithms' performances are greatly better than that of the traditional fixed sub-carrier allocation method.

The primary objective of this proposal is to minimize the battery drain and to maximize the compatibility of the device so that the complexity of the device is much more reduced to enhance the battery period considerably. In this paper we adopted a method for increasing the response time using a priority based algorithm along with Field Programmable Gate Array (FPGA) in Reconfigurable Computing System (RCS) to handle complex applications and to increase the efficiency and throughput of the system. A primary comparison was made with all existing algorithms namely First Come First Serve (FCFS), Round Robin, Shortest Job First (SJF) for a given set of processes by taking process delay as a core parameter. The result obtained from this analysis gave a clear picture that the objective can be achieved by decreasing the waiting time and by increasing the throughput. By achieving this task, multitasking between the applications or processes can be done frequently. By adopting these kind of scheduling algorithms with programmable gate array, there is a considerable improvement and performance of the device. Also, the life span of the device is increased which is considered as most important criteria for any users in computing environment.