Efficient handover management remains a critical challenge in dense urban cellular networks, where high cell density, user mobility, and diverse service demands increase the likelihood of unnecessary handovers and ping-pong effects. This paper leverages a real-world, multi-operator drive-test dataset of 30,925 labelled records collected within a 2 km area around Sunway City to investigate sequence-based deep learning approaches for handover detection and avoidance. We formulate handover prediction as a sequence problem and evaluate Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM), and Transformer architectures under Reference Signal Received Power (RSRP)-only and all-feature settings. The integration of multi-dimensional features significantly enhanced handover performance in dense urban cellular networks. The proposed GRU-based model achieved a remarkable 98% reduction in ping-pong handovers, alongside a 46.25% decrease in unnecessary handovers, outperforming the baseline RSRP-only approach which yielded a 22.19% reduction. Furthermore, the model demonstrated a 46% improvement in Time of Stay (ToS), indicating more stable user connections. With an inference time of just 0.91 seconds, the solution proves highly efficient and well-suited for real-time edge deployment scenarios. Compared to the conventional 3GPP A3 algorithm, these improvements demonstrate significant gains in mobility robustness and user Quality of Experience (QoE) improvement. The dataset is released to foster reproducibility and further research in intelligent mobility management for 5G and beyond.

LoRaWAN has proven helpful in many application areas, such as meteorological monitoring in sparsely populated areas. LoRaWAN End Nodes send data to a LoRaWAN Gateway, conveying it to network and application servers using an IP connection. In remote areas, connectivity is often unavailable, but these areas can provide a wealth of data valid for disaster prevention, wild animal tracking, climate assessment, and modeling, among others. We present a LoRaWAN Range Extender, which extends the coverage of existing gateways without requiring any modification to the existing LoRaWAN infrastructure. This device could double the achievable range of a standard LoRaWAN link or enable nodes to be serviced behind obstacles that prevent direct communication with the Gateway. The Range Extender must be within the communication reach of an existing LoRaWAN Gateway while also being reachable by the End Nodes of interest. It can be located in places without cellular coverage, and since it is cheaper to operate and install, it can lower both capital and operational expenses.

This article proposes a novel Airborne Internet of Things Network (AIN) system architecture for monitoring water quality, combining existing wireless technologies with the aid of a low altitude platform (LAP) to relay data over long distances in hilly terrain. The proposed system consists of water quality sensors, smart utility network (SUN) devices, long range (LoRa) wireless devices, an LAP air balloon, and Wi-Fi devices. A measurement campaign was conducted to assess the proposed system, focusing on the communication link reliability and the LAP stability and robustness. Several constraints, such as payload limit and safe weather conditions, were also highlighted for operating the LAP with extensive and reliable coverage. On the other hand, characterizing the wireless channel has become a crucial parameter for planning and deploying Internet of Things (IoT) applications. Accordingly, this work proposes a novel hybrid machine learning (ML)-based semi-empirical path loss (PL) model for LoRa wireless communication. The results validated the proposed system’s effectiveness, unique characteristics, and capability to monitor water quality in a harsh environment. Results also revealed a significant difference in packet delivery rate (PDR) for different gateway height and spreading factor (SF) configurations. For instance, switching SF7 to SF12 increased PDR by 28.7%. Meanwhile, increasing gateway height increased PDR by 29.2% for similar SF configurations. The evaluation also revealed that none of the established PL models are suitable to represent harsh tropical environments. Finally, the proposed model achieved nearly 90% prediction accuracy for testing samples and 95% accuracy for training and overall measurement samples, vastly outperforming conventional models.

Narrowband Internet of Things (NB-IoT) is expected to lead the way in wireless access technologies and support major 5G-based Internet of Things applications in the future. Since NB-IoT has yet to be fully deployed globally, there are only limited real-world performance evaluations available, particularly in the case of outdoor performance. Therefore, this study expanded on previous studies and comprehensively evaluated the performance of NB-IoT in the real world in terms of coverage parameters, path loss (PL), packet delivery rate (PDR), and latency limits. Numerical and detailed analyses were also performed to calculate power consumption and estimate the average battery life of NB-IoT, Sigfox, and LoRaWAN in relation to the various factors affecting power consumption. These three technologies were then compared in terms of power consumption. An overall PDR of 91.76% was achieved, indicating that NB-IoT can handle high data rates with minimal signal quality. NB-IoT performance was also found to correspond with theoretical assumptions on coverage and maximum range. However, depending on signal quality, latency was found to vary greatly, resulting in critical degradation of battery life efficiency. Although this study discovered that immense power savings could be achieved by applying critical power management strategies, achieving a long battery life for NB-IoT was not simple. LoRaWAN and Sigfox technologies proved to be more battery efficient than NB-IoT. In a one packet delivery per day scenario, LoRaWAN, Sigfox, and NB-IoT were found to have average battery lives of 1608.9, 1527.6, and 344.9 days, respectively.

With the promising advances in the telecommunication and automotive industries, there are increasing concerns on the reliability of Intelligent Transportation Systems (ITS) applications and standardization efforts. Nowadays, vehicles are empowered with innovative communications and sensing capabilities to accelerate next-generation Connected and Autonomous Vehicles (CAV) or Vehicle-to-Everything (V2X) communications. Furthermore, V2X is based on many radio access technologies including Dedicated Short-Range Communications (DSRC), Cellular-V2X, and millimeter-wave. It is expected that a single technology is incapable to support the diverse QoS and reliability requirements of vehicular safety and non-safety applications. Therefore, recent research works have investigated and developed different approaches to enable multi-radio access technologies (Multi-RAT) in V2X networks to support these multitudes of requirements. In addition, the heterogeneity of diverse radio access technologies and rigidity in their deployment increases the complexity of the network management. Complications may also arise from inefficient resource utilization due to the complexity of an optimum RAT selection or multi-link establishment through Multi-RATs. Therefore, a global monitoring paradigm such as Software-Defined Vehicular Network (SDVN) has been identified as a solution to reduce this bottleneck, by adding flexibility and agility to the vehicular network. This paper extensively reviews recent related works on Multi-RAT V2X networks focusing on the opportunistic selection mechanism of RAT, allocation of radio resources, and simultaneous establishment of multi-link over a heterogeneous network. Consequently, we have outlined the SDVN architecture, layers, features, and significance towards enhancing the performance of such Multi-RAT networks. Finally, several potential challenges with probable solutions and opportunities are discussed.

The use of Machine-to-Machine (M2M) applications is increasing in Malaysia. Internet of Things (IoT) is the driving force for M2M applications. This M2M application can create a smart environment with the application that facilitates the community. To create a smart city in Malaysia, existing problems must be solved with Low Power Area Network Technology (LPWAN). LPWAN technology consists of three leading technologies, namely LoRa, SigFox, and NB-IoT. LPWAN offers low power consumption, long battery life, long-distance low-rate transmission, and low latency and cost. This study investigates the performance coverage of the existing LPWAN communication network in Kuala Lumpur, Malaysia City based on three potential applications: traffic light management system, domestic waste disposal management system, and public transport control system. Next, plan and predict the LPWAN communication coverage network and selected M2M applications in Kuala Lumpur. The results show that LoRa technology performance is optimal for the public transport system and the domestic waste disposal management system, while for the traffic light system is Sigfox technology based on the optimal value of the link budget for each radio link (-dBm).

This paper proposes a new method based on a 2D Angle of Arrival (2D-AOA) estimation that employs 3D beamforming to eliminate the effect of interference in a Massive MIMO (M-MIMO) system. The interferences are the results of pilot contamination and spatial overlapping from nearby users. High resolution Azimuth and Elevation angles of the detected signals from Uniform Rectangular Array (URA) are used to separate the desired signal from the interfering ones without causing any change in the pilot construction of training signals. Additionally, tilt angle adaptation is employed at the base station to maximize the spectral efficiency of multi-cell M- MIMO. The performance of the proposed method is evaluated and compared with that of the conventional methods of 2D beamforming in terms of achievable sum rate. Results of the simulation demonstrate that the 3D beamforming achieved a 55% sum rate gain due to the elimination of both pilot contamination and spatial overlapping in comparison to the 24% sum rate gain achieved via the 2D beamforming method which only eliminates pilot contamination. This shows the potential of the proposed method in eliminating a large proportion of cell interference.

Recent works on the future 5G cellular communication proposed that the enormous raw bandwidth availability of the millimeter-wave (mmWave) frequencies is an excellent opportunity to increase data capacity and channel capacity. However, mmWave transmission requires beamforming to overcome the high path loss, as well as other losses due to rain and oxygen absorption and higher noise floor associated with larger bandwidth. This paper presents a comparison on the channel statistics of a mmWave systems operating using isotropic antenna against phased array beamforming in the 60GHz IEEE 802.11ad standard. Real world maps are incorporated into a 3-D mmWave ray-tracing tool for the purpose of employing realistic channel matrices into an 802.11ad bit level simulator. Different environments such as dense urban, urban, highway and residential area in Bristol and Malaysia are considered. Besides that, the throughput performance considering various MCS modes are also presented for both Orthogonal Frequency Division Multiplexing (OFDM) and Single Carrier (SC) transmissions.

Massive multiple-input multiple-output (MIMO) systems combined with beamforming antenna array technologies are expected to play a key role in next-generation wireless communication systems (5G), which will be deployed in 2020 and beyond. The main objective of this review paper is to discuss the state-of-the-art research on the most favourable types of beamforming techniques that can be deployed in massive MIMO systems and to clarify the importance of beamforming techniques in massive MIMO systems for eliminating and resolving the many technical hitches that massive MIMO system implementation faces. Classifications of optimal beamforming techniques that are used in wireless communication systems are reviewed in detail to determine which techniques are more suitable for deployment in massive MIMO systems to improve system throughput and reduce intra- and inter-cell interference. To overcome the limitations in the literature, we have suggested an optimal beamforming technique that can provide the highest performance in massive MIMO systems, satisfying the requirements of next-generation wireless communication systems.

Rendezvous is a prerequisite and important process for secondary users (SUs) to establish data communications in cognitive radio networks (CRNs). Recently, there has been a proliferation of different channel hopping- (CH-) based schemes that can provide rendezvous without relying on any predetermined common control channel. However, the existing CH schemes were designed with omnidirectional antennas which can degrade their rendezvous performance when applied in CRNs that are highly crowded with primary users (PUs). In such networks, the large number of PUs may lead to the inexistence of any common available channel between neighboring SUs which result in a failure of their rendezvous process. In this paper, we consider the utilization of directional antennas in CRNs for tackling the issue. Firstly, we propose two coprimality-based sector hopping (SH) schemes that can provide efficient pairwise sector rendezvous in directional antenna CRNs (DIR-CRNs). Then, we propose an efficient CH scheme that can be combined within the SH schemes for providing a simultaneous sector and channel rendezvous. The guaranteed rendezvous of our schemes are proven by deriving the theoretical upper bounds of their rendezvous delay metrics. Furthermore, extensive simulation comparisons with other related rendezvous schemes are conducted to illustrate the significant outperformance of our schemes.

Network MIMO is a feasible technique that can significantly improve the performance of wireless communication systems by canceling the Inter-cell Interference (ICI). Dynamic Fractional Frequency Reuse (DFFR) is the technique to mitigate ICI in LTE-Advanced system, which improve throughput and capacity, especially for the cell-edge users (CEUs). Recent research has shown that the impact of DFFR scheme on system performances has already studied and can provide significant gains in term of outage probability and network sum rate throughput. This paper presents a performance investigation of a DFFR scheme in a Network MIMO configuration based on an LTE-A downlink transmission environment. This paper also aims to enhance cell edge throughput and capacity by improving water filling algorithm for power allocation (PA). The proposed PA strategy is to maximize the performance of CEUs which commonly incur considerable ICI. Furthermore, the proposed method has been compared to the Frequency Reuse, Fractional Frequency Reuse (FFR) and other conventional DFFR schemes. Results show that the proposed scheme present superior performances of the throughput by 60% and capacity by 42% compared to the other schemes.

The main criteria for designing the upcoming cellular systems are: More network capacity and less energy consumption. Recently, distributed antenna system (DAS) has received considerable attention due to its potential to provide higher spectral efficiency and uniform coverage for cellular networks. In this regard, this article compares the performance of DAS with centralized antenna system (CAS) in LTE-Advanced system in term of cell throughput and energy efficiency (EE), where practical restrictions such as out-of-cell interference, path-loss, and small-scale fading are taken into account. Furthermore, the EE degradation is investigated under two different sleep-mode scenarios (moderate and low loaded networks) where different number of antennas are activated. Finally, we investigate the impact of channel bandwidth enhancement on the compensation of EE degradation due to the antenna muting during the sleep modes. The results reveal that DAS considerably outperforms CAS in term of EE (up to 56.6%). Furthermore, the simulation results show that during the sleep modes, by optimally assigning channel bandwidth, the EE-loss, not only can be compensated, but also EE can be significantly improved, where the proposed methodology guarantees a considerable power-saving for the cellular network (up to 27.63%).

Multiple-Input Multiple-Output (MIMO) technology can increase the channel capacity and mitigate the effect of multipath fading in a wireless transmission. Orthogonal Frequency Division Multiple Access (OFDMA), however, offers high flexibility in radio resource management according to the Quality of Service (QoS) demands of different users. The combination of MIMO and OFDMA techniques, MIMO-OFDMA, has become a strong candidate for Long Term Evolution (LTE) downlink transmissions. A full feedback scheme has been known to increase the uplink overhead requirement. Therefore, a partial feedback scheme utilizing DFT-based codebook precoding is considered to exploit spatial diversity from the multiuser (MU)-MIMO. In addition, the frequency diversity will be exploited by introducing an interference-aware subcarrier allocation scheme to reduce the effect of self-interference, which occurs due to an increasing spatial correlation between the communicating MIMO antennas. A full feedback scheme is also considered in the simulation for comparison. The results have shown that the partial feedback scheme had robust Bit Error Rate (BER) performance, even when simulated in a fully correlated channel without an imposed higher feedback requirement to the base controller.

In this paper, a new trend of Space Time Block Code-Orthogonal Frequency Division Multiplexing (STBC-OFDM) was proposed. First, introduce brief description of the conventional (STBC-OFDM) scheme. Second, introduce the efficient and low complexity scheme of a STBC-OFDM, where both encoder and decoder lay in the time domain. This scheme does not require channel knowledge either at the transmitter or receiver. The decoding algorithm is based on generalized maximum-likelihood sequence estimation. The performance of the proposed scheme was investigated over two-tap Rayleigh fading channels. The simulation results show the performance of proposed STBC-OFDM scheme definitely outperforms conventional STBC-OFDM scheme on fading channel for different Doppler frequency (fD).

The integration of wireless worldwide interoperability for microwave access network (WiMAX and Long Term Evolution (LTE) in an all IP based heterogeneous networks that require seamless mobility is predicated on enabling the connection and retrieval of data by a mobile user not mindful of the medium or technology used. This phenomenon facilitates freedom of movement while maintaining service continuity. However, the interoperability between multiple access technologies should be able to realize the vision of 4G technology and beyond to allow mobile user equipment (UE) to roam freely when intersecting the cell-boundaries of different network platforms without losing the service. To achieve such task, a proposed mobility management system designed to detect conditions of the network early enough and effect changes to handover parameters while maintaining the network connectivity is being highlighted. The proposed system investigates how the signal strength threshold (RSSTh) influences handover decision for a prioritized network with regards to distance and velocity. Computer simulation based on a designed algorithm for vertical handover optimization is being implemented to trigger the inter-radio access technology (RAT) handover for evaluating the performance of next generation wireless network systems. The results show that the prioritized network stand to be the preferred network as the UE is connected to it most of the time.

There are two known MIMO transmission scheme in the wireless link-level research: Space-Time Coding (STC) and Spatial Multiplexing (SM). STC aims to achieve maximum antenna diversity and improve wireless link reliability, while SM, on the other hand provides a capability for increasing the data rate by higher spectral efficiencies, i.e. more bits/s/Hz of bandwidth. Most MIMO simulations consider ideal transmission spatial subchannels condition, whereby the fading correlation between each spatial subchannel is uncorrected with uniform Rayleigh's distribution. However, in a more realistic propagation environment, spatial correlation does exist between antenna pairs and affects the MIMO transmission link, resulting in reduced capacity and loss of Bits Error Rate (BER). The main aim of this paper is to investigate the effect of spatial interference due to spatially correlated MIMO subchannels by employing a dynamic subcarrier allocation, based on the Orthogonal Frequency Division Multiple Access (OFDMA) transmission scheme. Focus is given in the downlink path, since the Mobile Station (MS) is expected to benefit from the rich multiuser diversity gain given from the dynamic subcarrier allocation. From the simulation results, the BER performance between both the STC and SM scheme will be analyzed to further understand the limitation in transmission under different spatial correlation.

Multiple-Input Multiple-Output (MIMO) antennas and Multi-Carrier Code Division Multiple Access (MC-CDMA) are very promising candidates for simultaneous utilize in 4G systems, since they attain robustness, high spectral efficiency, and high data rates in rich scattering environments. This paper proposes an efficient hybrid detection algorithm for a downlink MC-CDMA system based on Orthogonal Frequency Division Multiplexing (OFDM). The proposed algorithm combines Genetic Algorithm-assisted Multiobjective Optimization Problem Solutions (GAMOPS) with Simplified Local Search (SLS) technique, which accelerate the search process to locate the exact global optimum throughout the iterative Linear Minimum Mean Square Error (LMMSE) approach, so called Hybrid GAMOPS-SLS (HGS) algorithm. The HGS algorithm contributes steadfastly to an accurate system design and evaluation in the framework of a practical MC-CDMA system. Beneath high order modulation, the simulation results are presented to exhibit an improved Bit Error Rate (BER) performance up to 8.2 dB and reducing of computational complexity order in terms of floating point operations (flops) by at least one order of magnitude at joint channel estimation and multiuser detection as well as intense trade-off between them.

One of the efficient ways to transmit high data rate in a wireless network is by employing a multiple antenna transmission scheme, known as the multiple-input multiple-output (MIMO). One of the MIMO schemes, known as Spatial Multiplexing (SM) relies on the linear independence data streams from different transmit antennas to exploit the channel capacity. Consequently, SM suffers considerably from the effect of spatial correlation, also known as self-interference in the literature, thus become one of the limiting factor in achieving the capacity benefit that SM offers. In an attempt to increase the robustness of the SM transmission for deployment in wide range of correlated channels, the use of dynamic subcarrier allocation (DSA) in a downlink Orthogonal Frequency Division Multiple Access (OFDMA) system is investigated. The Effective Signal-to-Interference-and-Noise Ratio (ESINR) metric is used as the performance metric to determine the subcarrier quality. The ESINR metric can be utilised for the subcarrier allocation process in order to exploit the multiuser diversity gain that can be offered in a correlated SM-OFDMA downlink system.

In a downlink transmission, users can benefit from the high capacity gain achieved by transmitting independent data streams from multiple antennas to multiple users sharing the same physical time-frequency resources. This technique is known as multiuser MIMO (MU-MIMO). However, performance of MU-MIMO is sensitive towards propagation imperfections, such as time dispersion and inter-stream interference due to antenna correlation. In this paper we investigate the performance of MU-MIMO operation in 3GPP-LTE downlink transmission by employing a novel multiuser allocation, known as dynamic subcarrier allocation (DSA) that aims to minimize the effect of antenna correlation from the knowledge of the Effective Signal-to-Interference-plus-Noise Ratio (ESINR) metric. The suboptimal scheme is especially attractive when the number of users is large in highly correlated channel conditions where it is able to minimize the effect of spatial correlation and thereby achieve improved BER performance.

For a single user with multiple receive antennas, co-antenna interference can be the dominant source of impairment in a Spatial Multiplex Orthogonal Frequency Division Multiple Access (SM-OFDMA) system, particularly when correlation exists between spatial sub-channels. By exploiting knowledge of the channel response and combining it with Dynamic Sub- Carrier Allocation (DSA), the algorithm proposed in this paper aims to reduce the effect of interference, while providing fair gain and maximizing the SINR across all users. Simulation results reveal that the proposed algorithm considers self-interference that exists between multiple antennas and is capable of achieving a capacity gain for every user with improved BER performance compared to previous work.