User Equipment Side Research Articles

Performance Analysis on Eigenmode Beamforming for Reduced Capability Device in Massive MIMO Systems

Recently, a new type of device that enables reduced capability (RedCap) has been identified and standardized in the fifth generation (5G) New Radio (NR). Because RedCap user equipment (UE) is designed to have low device cost and complexity compared with high-end devices, single-layer transmission is mainly considered for RedCap UE. For single-layer transmission, traditional eigenmode beamforming, which transmits a data stream through the maximum eigenmode direction, is applicable for base stations (BSs), and a simple matched filter can be used on the UE side. Under this operation scenario, the performance of eigenmode beamforming is analyzed in this study, and the effect of the number of UE antennas on the achievable rate is investigated. The asymptotic achievable rate for eigenmode beamforming with practical channel training for both the uplink and downlink is derived as a closed-form expression for any number of UE antennas <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> . For the analysis, the statistics of the maximum eigenvalue are derived using the Tracy-Widom distribution. The results of the analysis show that the maximum eigenvalue is a concave function in terms of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> , and there is an optimal number of UE antennas <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">opt</sub> that maximizes the achievable rate. Simulations verify the analytical results and show that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">opt</sub> maximizing the achievable rate decreases as the numbers of BS antennas and co-scheduled UEs increase.

RAT selection for IoT devices in HetNets: Reinforcement learning with hybrid SMDP algorithm

Due to the increasing deployment of heterogeneous networks (HetNets), the selection of which radio access technologies (RATs) for Internet of Things (IoT) devices such as user equipments (UEs) has recently received extensive attention in mobility management research. Most of existing RAT selection methods only optimize the selection strategies from the UE side or network side, which results in heavy network congestion, poor user experience and system utility degradation. In this paper the UE side and the network side are considered comprehensively, based on the game theory (GT) model we propose a reinforcement learning with assisted network information algorithm to overcome the crucial points. The assisted information is formulated as a semi-Markov decision process (SMDP) provided for UEs to make accurate decisions, and we adopt the iteration approach to reach the optimal policy. Moreover, we investigate the impacts of different parameters on the system utility and handover performance. Numerical results validate that our proposed algorithm can mitigate unnecessary handovers and improve system throughputs.

On the Impact of Frequency Discrepancy on Beamforming Performance in Millimeter-Wave Phased Array Antenna Systems

Multiple-input&#x2013;multiple-output (MIMO) is a key technology used to meet the requirements of 5G systems. In millimeter-wave (mmWave) bands, directional beamforming is applied at both the transmitter and the receiver to establish an efficient radio link. The mmWave bands specified in 5G specifications range from 24.25 to 40.0 GHz. Accordingly, different countries may allocate different bands to support 5G services because of the availability of the spectrum and the countries&#x2019; radio management policies. For international roaming, user equipment (UE) must support multiband operations based on a fixed antenna hardware structure that is designed to target a specific operating band. Hence, the frequency discrepancy that results from using different operating bands causes distortion in the achieved beamforming pattern. In this article, we investigate the impact of frequency discrepancy on beamforming performance in mmWave phased array antenna systems at the UE side, considering the resultant beam pattern and interference. In this effort, we studied three major side effects&#x2014;deviation of the beamforming direction, change in the effective array length, and change in the normalized interelement spacing. The numerical results indicate that a large frequency discrepancy causes severe distortion in the resultant beamforming pattern and introduces more interference into the system.

Joint polar with physical layer network coding and massive MIMO: performance analysis

Large spectral efficiency, reliability, coverage, and energy efficiency are all major requirements to meet the targets of fifth-generation (5G) and beyond communication networks. The transmitted signal is usually susceptible to errors that reduced reliability and throughput of the system. Physical layer network coding (PLNC) is a promising technology to achieve better throughput, low latency, and high transmission rate. This paper considers the combination of PLNC with polar coding using massive multi-input multi-output (MIMO) system to enhance the transmission reliability by reducing the bit error rate (BER) and improve system reliability. This arrangement is investigated in two-way wireless relay transmission over millimetre wave (mmWave) band channel model. The results of the extensive simulation tests demonstrated improvements in throughput and BER achieved using polar code with PLNC and a sufficient number of antenna elements in the mMIMO system. The BER performance of polar-coded PLNC arrangement outperformed PLNC without coding for 128 and 256 receiving antenna elements in the relay node regardless the number of antenna elements in the user equipment side. The tests showed that the combination of the polar code with PLNC and MIMO system is not encouraging at low Signal-to-noise ratio (SNR).

User Equipment Tracking for a Millimeter Wave System Using Vision and RSSI

In a mobile millimeter wave (mmWave) communication system, blockages cause disconnections or serious degradation of communications. Several techniques have been proposed to control radio links between multiple base stations based on blockage prediction using camera images to avoid these problems. However, blockage prediction requires continuously determining the position of user equipment (UE) with decimeter precision, which is difficult when sensors and resources on the UE side are not available, and there are many moving objects around the UE. To resolve this problem, we propose a UE tracking method that uses a received signal strength indicator (RSSI) and RGB-D camera images from the base station. The proposed method consists of a combination of visual tracking and reidentification of the UE using radio information and camera images. We use the synchronization of the RSSI variation with the occlusion on the image by movements of the UE and objects for reidentification. We evaluated the proposed method experimentally in an outdoor environment by simulating a communication area formed by mmWave band base stations. The proposed method achieved an 11.5% improvement in tracking accuracy compared with conventional visual tracking.

Impact and Calibration of Nonlinear Reciprocity Mismatch in Massive MIMO Systems

Time-division-duplexing massive multiple-input multiple-output (MIMO) systems estimate the channel state information (CSI) by leveraging the uplink-downlink channel reciprocity, which is no longer valid when the mismatch arises from the asymmetric uplink and downlink radio frequency (RF) chains. Existing works treat the reciprocity mismatch as constant for simplicity. However, the practical RF chain consists of nonlinear components, which leads to nonlinear reciprocity mismatch. In this work, we examine the impact and the calibration approach of the nonlinear reciprocity mismatch in massive MIMO systems. To evaluate the impact of the nonlinear mismatch, we first derive the closed-form expression of the ergodic achievable rate. Then, we analyze the performance loss caused by the nonlinear mismatch to show that the impact of the mismatch at the base station (BS) side is much larger than that at the user equipment side. Therefore, we propose a calibration method for the BS. During the calibration, polynomial function is applied to approximate the nonlinear mismatch factor, and over-the-air training is employed to estimate the polynomial coefficients. After that, the calibration coefficients are computed by maximizing the downlink achievable rate. Simulation results are presented to verify the analytical results and to show the performance of the proposed calibration approach.

5G Energy Efficiency Overview

It is a critical requirement for the future of 5G communication networks to provide high speed and significantly reduce network energy consumption. In the Fifth Generation (5G), wireless cellular networks, smartphone battery efficiency, and optimal utilization of power have become a matter of utmost importance. Energy-efficient networks along with an energy-saving strategy in mobile devices play a vital role in the mobile revolution. The goal of energy efficiency, apart from its ecological value, is also associated with the reduction of operational expenses for mobile network operators, as well as with greater customer satisfaction thanks to increased battery life. Battery and power are an area of significant challenges considering that smartphones are nowadays equipped with advanced technological network features and interfaces. These features require a lot of simultaneous power to make decisions and to transfer information between devices and networks to provide the best user experience. Furthermore, to meet the demands of increased data capacity, data rate, and to provide the best quality of service, there is a need to adopt energy-efficient architectures. The new strategies should not only focus on wireless base stations, which consumes most of the power, but it should also take into consideration the other power consumption elements for future mobile communication networks, including User Equipment (UE). In this paper, we do an overview of power consumption and improvements made so far on the networks and user equipment side and provide our proposals on how to overcome these power- European Scientific Journal, ESJ ISSN: 1857-7881 (Print) e - ISSN 1857-7431 January 2021 edition Vol.17, No.3 www.eujournal.org 316 hungry issues on the newly 5G systems.

Precoder and Spatial Compression Filter Designs for Uplink Cloud Radio Access Networks

This work considers an uplink cloud radio access network (C-RAN), and proposes a MIMO spatial compression filtering and which compressed symbols to upload at RRH side as well as MIMO precoding at UE (user equipment) side. The error rate performance of this proposed scheme is analyzed and closed-form analytical results are obtained. Based on the analytical results, we propose solutions for the spatial compression filter, compressed symbols and UE precoder. Fronthaul loading can be significantly reduced by the proposed MIMO spatial compression filter and compressed symbols; meanwhile this proposed scheme can greatly outperform conventional schemes under the same settings of fronthaul loading. Moreover, when the UE has multiple antennas, the performance can further be significantly improved by using the proposed UE precoder. Simulation results are provided to show the accuracy of the analytical results as well as the advantages of the proposed solutions in terms of error rate performance and reduced fronthaul loading.

Vertical handoff model in next generation wireless networks

The purpose of this research is to propose a scheme for making handoff decisions effectively. We propose a handoff decision strategy through a fuzzy logic system to perform a seamless handoff. We combine four types of determinants, namely, RSS (received signal strength), data rate, network latency, and user preferences as input metrics to our fuzzy inference engine. RSS is pre-processed first by the Kalman filter to get rid of noise. The logic of the inference engine is realized on the User Equipment side as a faster reaction to network dynamics. Our scheme performance is evaluated by simulating mobility scenarios through the context of move-out and move-in scenarios. Simulation results show that our scheme outperforms other approaches in terms of reducing unnecessary handoff for all cases.

Power Saving Techniques for 5G and Beyond

Energy efficiency is one of the key performance indicators in 5G New Radio (NR) networks targeted to support diversified use cases including enhanced mobile broadband (eMBB), massive machine type communications (mMTC) and ultra-reliable and low latency communications (URLLC). Trade-offs have to be carefully considered between energy efficiency and other performance aspects such as latency, throughput, connection densities and reliability. Energy efficiency is important for both user equipment (UE) side and base station side. On UE side, UE battery life has great impact on user experience. It is challenging to improve UE experience in other performance aspects without affecting battery life of 5G handsets. On the base station side, efficient network implementation is critical in both environmental and operation cost standpoints. To adapt different requirements and trade-offs, the 5G NR standard is designed to have great flexibility on network operation modes. This paper provides an overview on power saving techniques supported by 5G NR standards according to the current 5G standardization progress. It provides the 5G evolution path of the power saving techniques from the first release of 5G standard to the future beyond-5G releases. In addition to the existing standardized techniques, some major development trends of green communication and the future potential enhancements expected in the beyond-5G standards are discussed.

Introduction to the Computation Offloading from Mobile Devices to the Edge of Mobile Network

This paper introduces the concept of Small Cell Cloud (SCC) composed of multiple Cloud-enabled Small Cells (CeSCs), which provide radio connection for mobile User Equipment (UE) such as smart-phones or wearables such as smart glasses. Moreover, CeSCs host computations offloaded from UEs in a way similar to centralized cloud, yet different in its proximity to users. Proposed client-server architecture of SCC conveys mechanisms for moving offloaded computations from the UEs to CeSCs. Real-life implementation of the SCC architecture relies on custom-developed Offloading Framework which is responsible for low-level communication between the UE and the SCC. The Offloading Framework is accompanied by an Augmented Reality (AR) app, which employs intensive computations for discovery of places of interest. Such app is latency-sensitive, a~criterion which makes computation offloading beneficial due to its ability to decrease latency. The combination of the Offloading Framework and the AR app makes up an SCC testbed used for further performance evaluation. Numerous measurements are carried out to examine the impact of various parameters. Based on Proof-of-concept implementation and thorough measurements, it has been revealed that computation offloading can decrease overall latency as much as to 47% and energy consumption on the UE side to 56%.

Downlink Training in Cell-Free Massive MIMO: A Blessing in Disguise

Cell-free Massive MIMO (multiple-input multiple-output) refers to a distributed Massive MIMO system where all the access points (APs) cooperate to coherently serve all the user equipments (UEs), suppress inter-cell interference and mitigate the multiuser interference. Recent works demonstrated that, unlike co-located Massive MIMO, the \textit{channel hardening} is, in general, less pronounced in cell-free Massive MIMO, thus there is much to benefit from estimating the downlink channel. In this study, we investigate the gain introduced by the downlink beamforming training, extending the previously proposed analysis to non-orthogonal uplink and downlink pilots. Assuming single-antenna APs, conjugate beamforming and independent Rayleigh fading channel, we derive a closed-form expression for the per-user achievable downlink rate that addresses channel estimation errors and pilot contamination both at the AP and UE side. The performance evaluation includes max-min fairness power control, greedy pilot assignment methods, and a comparison between achievable rates obtained from different capacity-bounding techniques. Numerical results show that downlink beamforming training, although increases pilot overhead and introduces additional pilot contamination, improves significantly the achievable downlink rate. Even for large number of APs, it is not fully efficient for the UE relying on the statistical channel state information for data decoding.

Statistics-Assisted Beam Training for MmWave Massive MIMO Systems

Combined with massive multiple-input multiple-output technology, beamforming can effectively compensate the high path-loss of millimeter-wave signals and hence improve the received power at user equipment (UE). In order to establish the beam alignment between base station (BS) and UE, beam training (BT) is required to select appropriate beamforming vectors at both BS and UE sides. In general, a good trade-off between beamforming gain and BT overhead is critical to enhance the system performance. In this letter, a statistics-assisted beam training (SA-BT) scheme is proposed to reduce the BT overhead. Specifically, BS scans the candidate beams according to the descending order of the utilization frequency of each beam. Meanwhile, the BT procedure is finished when the beamforming gain at UE exceeds the pre-defined threshold. The theoretical analyses and the numerical simulations prove that the proposed scheme can reduce the BT overhead and hence improve the spectral efficiency significantly compared with the existing methodologies.

Multiband User Equipment Prototype Hardware Design for 5G Communications in Sub-6-GHz Band

Verification of physical (PHY) layer and medium access control (MAC) layer procedures of the fifth-generation (5G) specifications with real hardware prototypes is important in the commercialization of 5G mobile communication systems and is challenging as well. In this paper, we propose a flexible software-defined-radio (SDR)-based prototype hardware design for user equipment (UE), which can be used to implement novel 5G communication concepts. The proposed hardware architecture is featured by using a flexible baseband signal processing module and two independent programmable wideband radio frequency (RF) front ends that, respectively, cover the lower and higher frequencies of sub-6-GHz band. The flexibility of the baseband signal processing module is ensured by using four powerful field-programmable gate arrays (FPGAs) running the PHY entities and a powerful FPGA-based system-on-chip running the MAC entities. The flexibilities of the RF front ends lay in the facts that: 1) the design covers three sub-6-GHz frequency bands, that is, 2.5, 3.5, and 4.9 GHz; 2) it can support dual connectivity for the upcoming 5G networks; and 3) it enables carrier aggregation (CA) over up to three carriers to achieve 300-MHz bandwidth. Accordingly, this prototype is capable of verifying the complicated scheduling procedures, evaluating the sophisticated signal processing algorithms in both PHY and MAC layers, and supporting the 100-MHz 4T4R multiple-input multiple-output (MIMO) or 200-MHz 2T2R MIMO techniques. Experiments have been performed on 256-QAM modulated waveforms to assess transmission power, error vector magnitude, adjacent channel leakage ratio from the UE side, and peak data rates between a base station and the UE.

Power and energy optimization with reduced complexity in different deployment scenarios of massive MIMO network

SummaryWith the increase in the number of users, the role of massive MIMO has become more significant. But there is a significant increase in the power and energy consumption in the massive MIMO network for transmission, processing, and reception. Hence, the prior role is to reduce the power consumption and increase the energy efficiency of the network. In this paper, the work is done to reduce the power consumption, while maintaining the reduced complexity in the massive MIMO and small‐cell scenario, and to increase the energy efficiency, by optimizing the number of users and number of transmission antennas in the massive MIMO scenario. This paper has also found out the optimal values of the energy efficiency, number of transmission antennas, and number of users for a massive MIMO network in different deployment scenarios like indoor hotspot, ultradense, dense urban, urban, suburban, and rural areas in both single‐cell scenario and multicell scenario at the base station and user equipment side according to the ITU‐R M.2135 standard.

Not in My Neighborhood: A User Equipment Perspective of Cellular Planning Under Restrictive EMF Limits

The installation of base station (BS) sites is regulated by a variety of laws at international, national, and local levels. While international regulations are already severe, the national and local laws applied in many countries and regions follow precautionary principles and enforce electromagnetic field (EMF) constraints that are even more restrictive. This legal environment results in substantial constraints affecting the planning of cellular networks, as requests for new BS site installation are easily denied by national or local authorities. In this paper, we consider the problem of cellular planning under restrictive EMF limits from the user equipment (UE) viewpoint. We focus on outdoor urban areas and first evaluate the impact of the current, non-optimal network planning at the UE side through a quantitative measurement-driven analysis of the quality of service (QoS) observed by users in heterogeneous, large-scale urban scenarios. We then perform a qualitative assessment of the perceived QoS and generated EMF levels at one UE transferring data from/to a BS based on its position with respect to the serving BS. Finally, we run a what-if analysis by comparing the existing planning with the one where new BS sites can be installed, thanks to a relaxation of the restrictive EMF constraints. Our results clearly show that a cellular planning driven by restrictive EMF constraints forces UE to experience large distances from the serving BS, frequent non-line-of-sight conditions, and poor received signal. In turn, this entails a very negative combination of high electric field activity (EFA) levels generated by the UE and low QoS perceived by the user. We show that, by relaxing the restrictive EMF constraints, the problem could be sensibly mitigated with a positive impact on the UE channel conditions and consequently on the perceived QoS and the UE EFA.

Full-Duplex Small-Cell Networks: A Physical-Layer Security Perspective

We provide a theoretical study of physical (PHY)-layer security performance in full-duplex (FD) small-cell networks. Here, the multi-antenna base stations (BSs) and user equipments (UEs) follow from the homogeneous Poisson point process-based abstraction model. To facilitate FD communications, we take into account: 1) successive interference cancellation capability at the UE side via guard regions of arbitrary radii and 2) residual self-interference at the BS side using Rician fading distribution with arbitrary statistics. We investigate the small-cell network PHY-layer security performance in the presence of a Poisson field of eavesdroppers, under the different scenarios of passive and colluding eavesdropping. Considering linear zero-forcing beamforming, we characterize the downlink and the uplink ergodic secrecy rates and derive closed-form expressions for the different useful and interference signals statistics. In certain special cases of interest, we apply non-linear curve-fitting techniques to large sets of (exact) theoretical data in order to obtain closed-form approximations for the different ergodic rates and ergodic secrecy rates under consideration. Our findings indicate that the FD functionality, in addition to enhancing the spectral efficiency, can significantly improve the PHY-layer security performance, especially with the aid of multi-antenna communications and interference cancellation schemes.

A Multimetric Approach for Handoff Decision in Heterogeneous Wireless Networks

Seamless mobility and service continuity anywhere at any time are an important issue in the wireless Internet. This research proposes a scheme to make handoff decisions effectively in heterogeneous wireless networks using a fuzzy system. Our design lies in an inference engine which takes RSS (received signal strength), data rate, network latency, and user preference as strategic determinants. The logic of our engine is realized on a UE (user equipment) side in faster reaction to network dynamics while roaming across different radio access technologies. The fuzzy system handles four metrics jointly to deduce a moderate decision about when to initiate handoff. The performance of our design is evaluated by simulating move-out mobility scenarios. Simulation results show that our scheme outperforms other approaches in terms of reducing unnecessary handoff.

Multi-Cell Cooperative Scheduling for Network Utility Maximization With User Equipment Side Interference Cancellation

Downlink inter-cell interference is a major limiting factor in current cellular systems. Several trends exacerbate the interference problem: cells become denser, more heterogeneous, and are more randomly deployed. To tackle this problem, there are many pure network-side solutions proposed, e.g., eICIC and feICIC in 3GPP LTE. However, these solutions are less spectrally efficient because the interferer usually needs to mute or reduce power to keep its interference power to victims below a tolerable level. In this paper, we consider an alternative solution in which the user equipment may perform interference cancellation (IC). In theory, this is a more spectrally efficient scheme as compared with the pure network-side solutions. In practice, however, to fully exploit the benefit of IC, the network should adopt some IC-aware scheduling rules. We propose a multi-cell joint scheduling, joint rate selection and power allocation problem in an IC-enabled network, trying to maximize the network utility. To make our solutions practical and readily deployable, we consider different settings. We explore both theoretically optimal IC scheme and the more practical symbol-level IC. On the other hand, we propose both dynamic and semi-static solutions, and compare them. Our simulation results show that while the average throughput increases by only around 10%, cell edge users can gain more than 50%.

Sum Rate Analysis and Power Allocation for Massive MIMO Systems With Mismatch Channel

Massive multiple-input multiple-output (MIMO) has been regarded as one of the key technologies of fifth-generation cellular systems due to its excellent performance in spectral and energy efficiency, whose performance has also been widely studied. However, most related works focus only on the impact of the wireless channels. In fact, its performance is affected not only by the wireless channel but also by the transceiver radio frequency (RF) circuits. Random variation of RF gain would lead to a mismatch channel, where the downlink is not the transpose of the uplink in time-division duplex (TDD) mode. Therefore, the impact of the transceiver RF circuits should be considered when we evaluate the performance of the massive MIMO systems. In this paper, we develop a detailed analysis on the downlink sum rate of the massive MIMO systems and derive its closed-form expressions using maximum ratio transmission and zero-forcing (ZF) precoding. The derived results provide some good insight into how the system performance is affected by the RF mismatch parameters. Based on the analytical results, we further investigate the optimal power allocation scheme to maximize the sum rate subject to the total power constraint and lowest rate requirement. For the simplest case of user equipment side mismatch with the ZF precoding, we apply the water-filling solution, while for the other mismatch cases, we conduct a convex relaxation on the non-convex problem through lower bound inequality, variable substitution, and Taylor expansion techniques, before applying some convex optimization solving tools. In the end, we propose an iterative algorithm to successively improve the iterative results for approaching the optimal solution. Simulations demonstrate that, for the massive MIMO systems with RF mismatch, our power allocation schemes achieve significant capacity improvement relative to an equal power scheme, and it performs well for the ZF precoding in the case of the RF mismatch only at the base station.