Unnecessary Handover Minimization in Two-Tier Heterogeneous Networks

Ultra-dense deployment of small cells (SC) can be foreseen in 5G network under the coverage area of the macrocell (MC). A mobile user equipment (UE) should be able to discover adjacent SCs to perform the handover (HO). This process can be done by frequent neighbour cell scanning. However, extensive scanning for every SC in a dense deployment scenario is a resource wasting strategy, which results in a power dissipation of the UE battery and also lowers the throughput gain. This also means that a high number of SCs would be available for the UE to HO to. Hence, the probability of unnecessary HO will increase and in turn degrade the UE's quality of service (QoS). This paper aims to minimize unnecessary HOs in two tier heterogeneous network with dense deployment of SCs. In the proposed method, we utilise the actual distance between the UE and the SCs and the UE angle of movement to construct a shortened candidate list which helps in reducing the signal overhead of scanning and the number of unnecessary HOs. UE's movement velocity threshold based on average human walking speed is used to control the HO to the SC. Simulation results show that the proposed algorithm outperformed the conventional HO method with reduced unnecessary HOs and increased throughput for the network particularly for medium to high speed UEs resulting in good UE QoS

Heuristic Coordinated Beamforming for Heterogeneous Cellular Network

Heterogeneous cellular networks (HetNets) is key technology in 5G used to tackle the ever increasing demand of data rate. The most critical problem of HetNet is interference. In this paper, we utilize the coordinated beamforming technique to mitigate the interference problem. We also suggest that reference signal receive power (RSRP) based cell association scheme has limitation when applied to multi-tier cellular networks. Therefore, we propose a new cell selection approach for HetNets, which is based on average channel gain. Simulation results of our designed beamformers show improvement over other schemes in terms of achievable information rates per cell

Global Optimization of Weighted Sum-Rate for Downlink Heterogeneous Cellular Networks

It is envisioned that Heterogeneous cellular network is key technology in 5G that can be used to meet the ever increasing demand of data rate. The most critical problem of HetNet is interference. One of our objectives is to design beamformers to mitigate interference and achieve the maximum throughput while satisfying some power and interference constraints. In this paper we are able to determine the global solution of the non-convex NP-hard weighted sum-rate problem using branch and bound method. It involves searching for the best individual rates among many feasible rates achievable in the system that maximizes the weighted sum-rate of the system while fulfilling the power and interference constraints. Results obtained show that our proposed method outperformed other methods such as egoistic beamforming method and the relaxed convex optimization heuristic method which produces sub-optimal solution to the original non-convex problem

An Efficient Downlink Channel Estimation Approach for TDD Massive MIMO Systems

In this paper, channel estimation problem for downlink massive multi-input multi-output (MIMO) system is considered. Motivated by the observation that channels in massive MIMO systems may exhibit sparsity and the path delays vary slowly in one uplink-downlink process even though the path gains may be quite different, we propose a novel channel estimation method based on the compressive sensing. Unlike the conventional methods which do not make use of any a priori information, we estimate the probabilities that the paths are nonzero in the downlink channel by exploiting the channel impulse response (CIR) estimated from the uplink channel estimation. Based on these probabilities, we propose the Weighted Structured Subspace Pursuit (WSSP) algorithm to efficiently reconstruct the massive MIMO channel. Simulation results show that the WSSP could reduce the pilots number significantly while maintain decent channel estimation performance

Antenna Beam Pattern Modulation with Lattice Reduction Aided Detection

This paper introduces a novel transmission design for antenna beam pattern modulation (ABPM) with a low complexity decoding method. The concept of ABPM was first presented with the optimal maximum likelihood (ML) decoding. However, an ML detector may not be viable for practical systems when the constellation size or the number of antennas is large such as in massive multiple input multiple output (MIMO) systems. Linear detectors, on the other hand, have lower complexity but inferior performance. In this paper, we present the antenna pattern selection with a lattice reduction (LR) aided linear detector for ABPM to reduce the detection complexity with the bit error rate (BER) performance approaching that of ML while conserving low complexity. Simulation results show that even with this suboptimal detection, performance gain is achieved by the proposed scheme compared to different spatial modulation techniques using ML detection. In addition, to validate the results, an upper bound expression for BER is provided for ABPM with ML detection

Locating Small Cells Using Geo-located UE Measurement Reports & RF Fingerprinting

This paper proposes a number of methods to determine potential small cell site locations using geo-located UE measurement reports in order to maximise the traffic offload from the macrocell network onto the small cells. The paper also shows how the information contained within the measurement reports can be used to create “RF fingerprints#x201D; which in turn can be used to discard UE measurement reports with erroneous location information and by doing so increase the effectiveness of the small cell placement algorithm. Simulations are presented which suggest that when addressing traffic hotspots in central London using small cells with coverage radii of 50m and 100m, the gains provided by the placement algorithms using simple RF fingerprinting technique are significant for UE reports with large location errors (>100m RMS error) when compared to techniques not using RF fingerprinting

β-Ga2O3 solar-blind deep-ultraviolet photodetector based on a four-terminal structure with or without Zener diodes

A four-terminal photodetector was fabricated on the (2⎯⎯⎯012¯01)-dominant β-Ga2O3 thin film which was deposited in a plasma-assisted molecular beam epitaxy system. The suitability of this film for solar-blind DUV detection was proved by its transmission spectra. Moreover, the device operating in a specific voltage-current mode can accurately detect the DUV radiation both qualitatively and quantitatively. Accordingly, a dark/photo voltage ratio of 15 was achieved, which is comparable to that of previously-reported β-Ga2O3 interdigital metal-semiconductor-metal photoconductor. More importantly, the aperture ratio of our proposed device exceeds 80%, nearly doubling that of the conventional interdigital metal-semiconductor-metal devices including photoconductor and Schottky-type photodiode, which can intensively benefit the detection efficiency. Furthermore, it was found the dark/photo voltage ratio was nearly trebled with the assistance of two Zener diodes, and further enhancement can be expected by increasing the operating current and/or adopting Zener diodes with smaller Zener voltage. Therefore, this work provides a promising alternative for solar-blind DUV detection.published_or_final_versio

Human motion tracking based on complementary Kalman filter

Miniaturized Inertial Measurement Unit (IMU) has been widely used in many motion capturing applications. In order to overcome stability and noise problems of IMU, a lot of efforts have been made to develop appropriate data fusion method to obtain reliable orientation estimation from IMU data. This article presents a method which models the errors of orientation, gyroscope bias and magnetic disturbance, and compensate the errors of state variables with complementary Kalman filter in a body motion capture system. Experimental results have shown that the proposed method significantly reduces the accumulative orientation estimation errors

Corticomuscular coherence analysis on the static and dynamic tasks of hand movement

The synchronization between cortical motor and muscular activity can be revealed by corticomuscular coherence (CMC). This paper designed two neuromuscular activity paradigms of hand movement, i.e. static gripping task and dynamic finger moving task. The electroencephalography (EEG) from C3 and C4 channels and the surface electromyography (sEMG) from the flexor digitorum superficialis were collected simultaneously from 4 male and 4 female right-handed healthy young subjects. For the static griping task, CMCs during low-level forces under 4%, 8%, and 16% MVC (Maximal Voluntary Contraction) were investigated by using magnitude squared coherence calculated from EEGs and sEMGs. For the dynamic finger moving task, the time-frequency domain analysis was used to process dynamic data of temporary action in a period of 2 seconds and get the latency of the maximum CMC. The results of this study indicated that the force increasing within the low-level range in static task is associated with the enhanced CMC. The maximum amplitude of CMC occurred about 0.3–0.5s after the onset of hand movement. Subjects showed significant CMC performance both in static and dynamic task of hand movement.published_or_final_versio

Orientation distribution of cylindrical particles suspended in a turbulent pipe flow

2005-2006 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe