Performance enhancement of maximum ratio transmission in 5G system with multi-user multiple-input multiple-output

<span>The downlink multi-user precoding of the multiple-input multiple-output (MIMO) method includes optimal channel state information at the base station and a variety of linear precoding (LP) schemes. Maximum ratio transmission (MRT) is among the common precoding schemes but does not provide good performance with massive MIMO, such as high bit error rate (BER) and low throughput. The orthogonal frequency division multiplexing (OFDM) and precoding schemes used in 5G have a flaw in high-speed environments. Given that the Doppler effect induces frequency changes, orthogonality between OFDM subcarriers is disrupted and their throughput output is decreased and BER is decreased. This study focuses on solving this problem by improving the performance of a 5G system with MRT, specifically by using a new design that includes weighted overlap and add (WOLA) with MRT. The current research also compares the standard system MRT with OFDM with the proposed design (WOLA-MRT) to find the best performance on throughput and BER. Improved system results show outstanding performance enhancement over a standard system, and numerous improvements with massive MIMO, such as best BER and throughput. Its approximately 60% more throughput than the traditional systems. Lastly, the proposed system improves BER by approximately 2% compared with the traditional system.</span>

Beam division multiple access for millimeter wave massive MIMO: Hybrid zero-forcing beamforming with user selection

<p>Massive multiple-input multiple-output (MIMO) systems are considered a promising solution to minimize multiuser interference (MUI) based on simple precoding techniques with a massive antenna array at a base station (BS). This paper presents a novel approach of beam division multiple access (BDMA) which BS transmit signals to multiusers at the same time via different beams based on hybrid beamforming and user-beam schedule. With the selection of users whose steering vectors are orthogonal to each other, interference between users is significantly improved. While, the efficiency spectrum of proposed scheme reaches to the performance of fully digital solutions, the multiuser interference is considerably reduced.</p>

Efficient organization of nodes in wireless sensor networks (clustering location-based LEACH)

The rapid development of connected devices and wireless communication has enabled several researchers to study wireless sensor networks and propose methods and algorithms to improve their performance. Wireless sensor networks (WSN) are composed of several sensor nodes deployed to collect and transfer data to base station (BS). Sensor node is considered as the main element in this field, characterized by minimal capacities of storage, energy, and computing. In consequence of the important impact of the energy on network lifetime, several researches are interested to propose different mechanisms to minimize energy consumption. In this work, we propose a new enhancement of low-energy adaptive clustering hierarchy (LEACH) protocol, named clustering location-based LEACH (CLOC-LEACH), which represents a continuity of our previous published work location-based LEACH (LOC-LEACH). The proposed protocol organizes sensor nodes into four regions, using clustering mechanism. In addition, an efficient concept is adopted to choose cluster head. CLOC-LEACH considers the energy as the principal metric to choose cluster heads and uses a gateway node to ensure the inter-cluster communication. The simulation with MATLAB shows that our contribution offers better performance than LEACH and LOC-LEACH, in terms of stability, energy consumption and network lifetime.

Optimal Base Station Network Based on Topological Data Analysis

The decision of which base stations need to be removed due to the cost is always a difficult problem, because the influence on the cover rate of the network caused by the removal should be kept to a minimum. However, the common methods to solve this problem such as K-means Clustering show a low accuracy. Barcode, which belongs to TDA, has the possibility to show the result by identifying the Persistent Homology of base station network. This essay mainly illustrates the specific problem of optimal base station network, which applies the TDA(Topological Data Analysis) methods to find which base stations need removing due to the cost K-means Clustering and Topological Data Analysis methods were mainly used. With the simulated distribution of telecommunication users, K-means Clustering algorithm was used to locate 30 best base stations. By comparing the minimum distance between the results (K=25 and K=30), K-means Clustering was used again to decide base station points to be removed. Then TDA was used to select which 5 base stations should be removed through observing barcode. By repeating above steps five times, Finally the average and variance of cover area in original network, K-means Clustering and TDA were compared. The experiment showed that the average cover rate of original network was 81.20% while the result of TDA and K-means Clustering were 92.13% and 89.87%. It was proved by simulation that it is more efficient to use TDA methods to construct the optimal base station network.

An Enhanced Decoding Algorithm for Coded Compressed Sensing with Applications to Unsourced Random Access

Unsourced random access (URA) has emerged as a pragmatic framework for next-generation distributed sensor networks. Within URA, concatenated coding structures are often employed to ensure that the central base station can accurately recover the set of sent codewords during a given transmission period. Many URA algorithms employ independent inner and outer decoders, which can help reduce computational complexity at the expense of a decay in performance. In this article, an enhanced decoding algorithm is presented for a concatenated coding structure consisting of a wide range of inner codes and an outer tree-based code. It is shown that this algorithmic enhancement has the potential to simultaneously improve error performance and decrease the computational complexity of the decoder. This enhanced decoding algorithm is applied to two existing URA algorithms, and the performance benefits of the algorithm are characterized. Findings are supported by numerical simulations.

Hybrid Direction of Arrival Precoding for Multiple Unmanned Aerial Vehicles Aided Non-Orthogonal Multiple Access in 6G Networks

Unmanned aerial vehicles (UAV) have attracted increasing attention in acting as a relay for effectively improving the coverage and data rate of wireless systems, and according to this vision, they will be integrated in the future sixth generation (6G) cellular network. Non-orthogonal multiple access (NOMA) and mmWave band are planned to support ubiquitous connectivity towards a massive number of users in the 6G and Internet of Things (IOT) contexts. Unfortunately, the wireless terrestrial link between the end-users and the base station (BS) can suffer severe blockage conditions. Instead, UAV relaying can establish a line-of-sight (LoS) connection with high probability due to its flying height. The present paper focuses on a multi-UAV network which supports an uplink (UL) NOMA cellular system. In particular, by operating in the mmWave band, hybrid beamforming architecture is adopted. The MUltiple SIgnal Classification (MUSIC) spectral estimation method is considered at the hybrid beamforming to detect the different direction of arrival (DoA) of each UAV. We newly design the sum-rate maximization problem of the UAV-aided NOMA 6G network specifically for the uplink mmWave transmission. Numerical results point out the better behavior obtained by the use of UAV relays and the MUSIC DoA estimation in the Hybrid mmWave beamforming in terms of achievable sum-rate in comparison to UL NOMA connections without the help of a UAV network.

Design Radio Network Links to Provide Internet for Pupulation of San Andres de Llamellin-Ancash

In recent years being able to have access to the internet has become a tool not only to be able to communicate in the distance but it is a great tool to be able to feed knowledge, it is because of them that children have a great educational utility and after this pandemic in Peru it was necessary to close schools, to be able to give remote classes or virtual classes. To solve the problem, we propose to be able to design a network of radio links whereby means of a base station of emission and reception, with an antenna of sectorial type and directional antennas to be able to realize a Point – Multipoint link which will be able to manage the quality of signal by means of a routing with functions of control of speeds for each connection of each home. It was the result that the connections of the radio link at an average distance from the coverage that the network had the signal was better and that the connections that were very far or close to the coverage area had complications, but despite this the connections were sufficient to be able to maintain the virtual classes that is what was planned. It is recommended that for a better connection and complete coverage it would be to reinforce the broadcast base with more sectoral antennas in the network. Keywords- Radio link, Point - Multipoint, Router, Download speed, Upload speed.

A Novel Energy-Efficient, Static Scenario-Oriented Routing Method of Wireless Sensor Network Based on Edge Computing

In wireless sensor network (WSN), the energy of sensor nodes is limited. Designing efficient routing method for reducing energy consumption and extending the WSN’s lifetime is important. This paper proposes a novel energy-efficient, static scenario-oriented routing method of WSN based on edge computing named the NEER, in which WSN is divided into several areas according to the coverage of gateway (or base station), and each of the areas is regarded as an edge area network (EAN). Each edge area network is abstracted into a weighted undirected graph model combined with the residual energy of the sensor nodes. The base station (or a gateway) calculates the optimal energy consumption path for all sensor nodes within its coverage, and the nodes then perform data transmission through their suggested optimal paths. The proposed method is verified by the simulations, and the results show that the proposed method may consume about 37% less energy compared with the conventional WSN routing protocol and can also effectively extend the lifetime of WSN.

Wideband beamspace squint user grouping algorithm based on subarray collaboration

The beam direction constrained problem is one of the important issues to be solved in millimeter-wave (mmWave) wideband communications when serving multi-user with squint beams whose direction varies with frequency. In this paper, we improve the number of simultaneous users served by collaboratively transmitting squint beams among multi-subarray at the base station (BS) end in a downlink multi-user line-of-sight (LoS) scenario, and reduce the interference among co-channel squint beams by a beam domain approach. The optimization problem of maximizing the number of users served in the system by transmitting beams in the two-dimensional beamspace of the planar antenna subarray is proposed and its suboptimal algorithm is given. Finally, the feasibility of the proposed method and the performance of the proposed algorithm are verified by numerical simulations.

Online Teaching Wireless Video Stream Resource Dynamic Allocation Method considering Node Ability

At present, wireless network technology is advancing rapidly, and intelligent equipment is gradually popularized, which rapidly developed the mobile streaming media business. All kinds of mobile video applications have enriched people’s lives by carrying huge traffic randomly. Wireless networks (WNs) are facing an unprecedented burden, which allocates very important wireless video resources. Similarly, in WNs, the network status is dynamic and the terminal is heterogeneous, which causes the traditional video transmission system to fail to meet the needs of users. Hence, Scalable Video Coding (SVC) has been introduced in the video transmission system to achieve bit rate adaptation. However, in a strictly hierarchical traditional computer network, the wireless resource allocation strategy usually takes throughput as the only way to optimize the target, and it is terrible to make more optimizations for scalable video transmission. This article proposed a cross-layer design to enable information to be transmitted between the wireless base station and the video server to achieve joint optimization. To improve users’ satisfaction with video services, the wireless resource allocation problem and the video stream scheduling problem are jointly considered, which keep the optimization space larger. Based on the proposed architecture, we further study the design of wireless resource allocation algorithms and rate-adaptive algorithms for the scenario of multiuser transmission of scalable video in the Long-Term Evolution (LTE) downlink. Experimental outcomes have shown substantial performance enhancement of the proposed work.