Signal-to-interference-plus-noise Ratio Threshold Research Articles

Low complexity detection algorithms based on ADMIN for massive MIMO

This paper proposes the alternating direction method of multipliers-based infinity-norm (ADMIN) with threshold (ADMIN-T) and with percentage (ADMIN-P) detection algorithms, which make full use of the distribution of the signal to interference plus noise ratio (SINR) for an uplink massive MIMO system. The ADMIN-T and ADMIN-P detection algorithms are improved visions of the ADMIN detection algorithm, in which an appropriate SINR threshold in the ADMIN-T detection algorithm and a certain percentage in the ADMIN-P detection algorithm are designed to reduce the overall computational complexity. The detected symbols are divided into two parts by the SINR threshold which is based on the cumulative probability density function (CDF) of SINR and a percentage, respectively. The symbols in higher SINR part are detected by MMSE. The interference of these symbols is then cancelled by successive interference cancellation (SIC). Afterwards the remaining symbols with low SINR are iteratively detected by ADMIN. The simulation results show that the ADMIIN-T and the ADMIN-P detection algorithms provide a significant performance gain compared with some recently proposed detection algorithms. In addition, the computational complexity of ADMIN-T and ADMIN-P are significantly reduced. Furthermore, in the case of same number of transceiver antennas, the proposed algorithms have a higher performance compared with the case of asymmetric transceiver antennas.

Resource Allocation for a Secure SWIPT Network Based on a Quantitative Energy Harvesting Mechanism.

Simultaneous wireless information and power transfer (SWIPT) technology can effectively extend the lifecycle of energy-constrained networks. In order to improve the energy harvesting (EH) efficiency and network performance in secure SWIPT networks, this paper studies the resource allocation problem based on the quantitative EH mechanism in the secure SWIPT network. Based on a quantitative EH mechanism and nonlinear EH model, a quantified power-splitting (QPS) receiver architecture is designed. This architecture is applied in the multiuser multi-input single-output secure SWIPT network. With the goal of maximizing the network throughput, the optimization problem model is established under the conditions of meeting the legal user's signal-to-interference-plus-noise ratio (SINR), EH requirements, the total transmit power of the base station, and the security SINR threshold constraints. Due to the coupling of variables, the problem is a nonconvex optimization problem. To deal with the nonconvex optimization problem, a hierarchical optimization method is adopted. Firstly, an optimization algorithm based on the optimal received power of EH circuit is proposed, and a power mapping table is constructed through the optimization algorithm, from which the optimal power ratio to meet the user's EH requirements is obtained; then, the nonconvex problem is transformed into a convex problem by using variable substitution, semidefinite relaxation, dichotomous optimization, etc. The simulation results show that compared with the power splitting receiver architecture, the input power threshold range of the QPS receiver architecture is larger, which can avoid the EH circuit falling into the saturated working area and maintain high network throughput.

Non-Orthogonal Multiple Access for UAV-Aided Heterogeneous Networks: A Stochastic Geometry Model

In this work, we explore the potential benefits of deploying unmanned aerial vehicles (UAVs) as aerial base stations (ABSs) with sub-6GHz bands and small cells terrestrial base stations (TBSs) with millimeter wave (mmWave) bands in a hybrid heterogeneous networks (HetNets). A flexible non-orthogonal multiple access (NOMA) based user association policy is proposed. By using the tools from stochastic geometry, new analytical expressions for association probability, coverage probability and spectrum efficiency are derived for characterizing the performance of UAV-aided HetNets under an appropriate Air-to-Ground (A2G) channel model and the Ground-to-Ground (G2G) channels with a LoS ball blockage model. Finally, we provide insights on the proposed hybrid HetNets by numerical results. We confirm that i) the proposed NOMA enabled HetNets is capable of achieving superior performance compared with the OMA enabled ABSs by setting power allocation factors and targeted signal-to-interference-plus-noise ratio (SINR) threshold properly; ii) there is a tradeoff between the association probabilities and the spectrum efficiency in the NOMA enabled ABSs tier; iii) the coverage probability and spectrum efficiency of the NOMA enabled ABSs tier is largely affected by the imperfect successive interference cancellation (ipSIC) coefficient, power allocation factors and SINR threshold; iv) compared with only sub-6GHz ABSs, mmWave enabled TBSs are capable of enhancing the spectrum efficiency of the HetNets when the mmWave line-of-sight (LoS) link is available.

A Methodology for Abstracting the Physical Layer of Direct V2X Communications Technologies

Recent advancements in vehicle-to-everything (V2X) communications have greatly increased the flexibility of the physical (PHY) and medium access control (MAC) layers. This increases the complexity when investigating the system from a network perspective to evaluate the performance of the supported applications. Such flexibility, in fact, needs to be taken into account through a cross-layer approach, which might lead to challenging evaluation processes. As an accurate simulation of the signals appears unfeasible, a typical solution is to rely on simple models for incorporating the PHY layer of the supported technologies based on off-line measurements or accurate link-level simulations. Such data are, however, limited to a subset of possible configurations, and extending them to others is costly when not even impossible. The goal of this paper is to develop a new approach for modeling the PHY layer of V2X communications that can be extended to a wide range of configurations without leading to extensive measurement or simulation campaigns at the link layer. In particular, given a scenario and starting from results in terms of the packet error rate (PER) vs. signal-to-interference-plus-noise ratio (SINR) related to a subset of possible configurations, we first approximated the curves with step functions characterized by a given SINR threshold, and we then derived one parameter, called implementation loss, that was used to obtain the SINR threshold and evaluate the network performance under any configuration in the same scenario. The proposed methodology, leading to a good trade-off among the complexity, generality, and accuracy of the performance evaluation process, was validated through extensive simulations with both IEEE 802.11p and LTE-V2X sidelink technologies in various scenarios. The results first show that the curves can be effectively approximated by using an SINR threshold, with a value corresponding to 0.5 PER, and then demonstrate that the network-level outputs derived from the proposed approach are very close to those obtained with complete curves, despite not being restricted to a few possible configurations.

Decentralized Power Control for an ALOHA-Type Random Multiple Access System with Short Packet Transmission

Machine to machine communication is an important scenario in a 6G communication network. Random multiple access has recently been revisited and considered a key technology for machine to machine communication scenarios due to many advantages such as without coordination setup time. It is a regret that packet collision probability will be extremely higher for random multiple access when massive devices randomly accessing base station. Decentralized power control is an efficient scheme in random multiple access systems which can support intraslot successive interference cancellation to recover multiple collided packets at receivers. However, existing studies of decentralized power control for random multiple access are with the assumption that blocklength of transmitted packets is infinite, which neglects that machine to machine communication is characterized by finite blocklength transmission (i.e., short packet) in 6G. This paper focuses decentralized power control with short packet transmission in random multiple access systems. First, the closed-form expression of signal to interference plus noise ratio (SINR) threshold for short packets is derived. Then, decentralized transmission power profile is defined based on derived SINR threshold of short packets, which can support intraslot successive interference cancellation deciding at receivers for an ALOHA-type random multiple access system. Further, we propose derivation method to maximize system throughput, which can reduce optimization cost. Theoretical findings in this paper can provide valuable benchmark for short packet transmission with decentralized power control in random multiple access systems.

Near-ML Detection Based on Multilevel SINR Thresholding for Mode Division Multiplexing Transmission With Mode-Dependent Loss

The probability distribution of the signal-to-interference plus noise ratio (SINR) is analyzed and approximated by the generalized gamma distribution for mode-dependent loss (MDL)-impaired fiber links. Based on the characteristics of SINR, an improved reduced-search algorithm (IRS) based on multilevel SINR thresholding (IRS-MST) is proposed. IRS-MST dynamically determines the size of the search space for each mode based on multiple SINR thresholds. Furthermore, a compounding function is used to balance the size of the search space and performance. Simulation results show that IRS-MST can achieve near ML performance for different MDLs. Compared to the conventional IRS algorithm, the complexity of IRS-MST is approximately 5.4 times smaller than that of the IRS.

Multi-Tier Variable Height UAV Networks: User Coverage and Throughput Optimization

Unmanned aerial vehicles (UAVs) are increasingly considered to act as base stations (BSs) for the future wireless networks. Some of the crucial UAV-assisted network design challenges are the network coverage, throughput, and energy efficiency. Therefore, fast, low-complexity, and efficient UAV placement and resource allocation strategies are imperative. This paper presents a novel variable height multi-UAV deployment strategy to exploit the 3D flexibility of UAVs as BSs. We propose a multi-tier variable height UAV-based network deployment and compare its performance with the state-of-the-art equal height deployment. Height optimization is performed to deliver energy efficiency and throughput maximization for each cell. The results show that our proposed method is more energy-efficient in a multi-cell UAV network than the most widely used height optimization method in the literature. In UAV networks, users at the cell edges can receive very poor signal-to-interference-plus-noise ratio (SINR) levels due to interfering UAVs. To cope with this problem, we adopt a fractional frequency reuse (FFR) scheme to compensate low SINR levels. We optimize the SINR threshold corresponding to each cell to maximize their spectral efficiency (SE), thereby improving the network’s area spectral efficiency (ASE). The numerical results show that the proposed deployments provide significant gains in coverage density, SINR coverage probability, rate coverage, and ASE compared to equal height benchmark scheme. As the number of UAVs increases, the number of tiers need to increase to preserve the rate coverage of the network. Moreover, the performance of the proposed variable height model is expected to converge to that of equal height cellular design for a large number of UAVs.

Interference and Coverage Modeling for Indoor Terahertz Communications with Beamforming Antennas

Abstract A general framework to investigate the interference and coverage probability is proposed in this paper for indoor terahertz (THz) communications with beamforming antennas. Due to the multipath effects of THz band (0.1–10 THz), the line of sight and non-line of sight interference from users and access points (APs) (both equipped with beamforming antennas) are separately analyzed based on distance-dependent probability functions. Moreover, to evaluate the effects of obstacles in real applications, a Poisson distribution blockage model is implemented. Moreover, the coverage probability is derived by means of signal to interference plus noise ratio (SINR). Numerical results are conducted to present the interference and coverage probability with different parameters, including the indoor area size, SINR threshold, numbers of interfering users and APs and half-power bandwidth of beamforming antenna.

Modeling and Analysis for Data Collection in Duty-Cycled Linear Sensor Networks With Pipelined-Forwarding Feature

Due to the vast demand for monitoring a structure or area in linear topology, linear sensor networks (LSNs) have recently attracted plenty of attention. Since sensor nodes are usually battery-powered, duty-cycling techniques have been widely studied to improve energy efficiency, which, however, introduces a significant issue known as sleep latency. Thereafter pipelined forwarding has been proposed in the literature as a promising way to alleviate this issue. This paper focuses on interference analysis for data collection services in a multihop LSN running a duty-cycling and pipelined-forwarding protocol, where multiple concurrent transmissions along a data collection path can severely interfere with each other. We first obtain the nodal distance distributions associated with all concurrent transmissions. Based on the obtained distance distributions and the path-loss model in an interference-limited environment, we analyze the distributions of signal-to-interference-plus-noise ratio (SINR) and link capacity. The obtained SINR distribution indicates the link outage probability at a given SINR threshold. By investigating the transmission which receives the strongest cumulative interference, our model can provide useful guidelines for duty cycle setting to achieve a desired network performance.

Performance Optimization for D2D Communications With Opportunistic Relay and Physical-Layer Network Coding

In this paper, we investigate the joint signal to interference plus noise ratio (SINR) thresholds optimization and resource allocation to maximize the sum-rate of Device-to-Device (D2D) communications while still retaining the rate requirements for active cellular users (CUs), when the inactive CUs are used as opportunistic relays under three operational modes: without using network-coding (NNC), using traditional high-layer network-coding (HNC), and using physical-layer network-coding (PNC). Under Rayleigh fading, we show that, given the selections of relays, this sum-rate maximization in no-relay scheme, NNC, HNC, and PNC opportunistic relay schemes can be formulated as a mixed integer non-linear programming (MINLP), which is NP-hard in general. To find the solution to the MINLP, we propose a two-step approach to solve the problem: 1) for each possible pairing of a D2D pair and a CU, we derive the optimal SINR thresholds to obtain the maximum transmission rate of the D2D pair while satisfying the rate requirement of the CU; 2) based on the maximum transmission rates of D2D pairs for each possible pairing in the first step, we develop a bipartite-matching method to find the optimal pairing CUs for D2D pairs. Finally, according to the solution to the MINLP, we propose an iterative relay selection algorithm to find out the relays that can further improve the sum-rate of D2D communications. Extensive simulation results demonstrate that, compared with the scenario without relaying, the NNC, HNC, and PNC opportunistic relay schemes achieve a maximum performance enhancement of 106%, 138%, and 168%, respectively.

Scheduling Policies for Federated Learning in Wireless Networks

Motivated by the increasing computational capacity of wireless user equipments (UEs), e.g., smart phones, tablets, or vehicles, as well as the increasing concerns about sharing private data, a new machine learning model has emerged, namely federated learning (FL), that allows a decoupling of data acquisition and computation at the central unit. Unlike centralized learning taking place in a data center, FL usually operates in a wireless edge network where the communication medium is resource-constrained and unreliable. Due to limited bandwidth, only a portion of UEs can be scheduled for updates at each iteration. Due to the shared nature of the wireless medium, transmissions are subjected to interference and are not guaranteed. The performance of FL system in such a setting is not well understood. In this paper, an analytical model is developed to characterize the performance of FL in wireless networks. Particularly, tractable expressions are derived for the convergence rate of FL in a wireless setting, accounting for effects from both scheduling schemes and inter-cell interference. Using the developed analysis, the effectiveness of three different scheduling policies, i.e., random scheduling (RS), round robin (RR), and proportional fair (PF), are compared in terms of FL convergence rate. It is shown that running FL with PF outperforms RS and RR if the network is operating under a high signal-to-interference-plus-noise ratio (SINR) threshold, while RR is more preferable when the SINR threshold is low. Moreover, the FL convergence rate decreases rapidly as the SINR threshold increases, thus confirming the importance of compression and quantization of the update parameters. The analysis also reveals a trade-off between the number of scheduled UEs and subchannel bandwidth under a fixed amount of available spectrum.

Optimum Deployment of Multiple UAVs for Coverage Area Maximization in the Presence of Co-Channel Interference

The use of the unmanned aerial vehicle (UAV) as the aerial base stations can provide wireless communication services in the form of UAV-based small cells (USCs). Thus, the major design challenge that needs to be addressed is the coverage maximization of such USCs in the presence of co-channel interference generated by multiple UAVs operating within a specific target area. Consequently, the efficient deployment strategy is imperative for USCs while optimizing the coverage area performance to compensate for the impact of interference. To this end, this paper presents a coordinated multi-UAV strategy in two scenarios. In the first scenario, symmetric placement of UAVs is assumed at a common optimal altitude and transmit power. In the second scenario, asymmetric deployment of UAVs with different altitudes and transmit powers is assumed. Then, the coverage area performance is investigated as a function of the separation distance between UAVs that are deployed in a certain geographical area to satisfy a target signal-to-interference-plus-noise ratio (SINR) at the cell boundary. Finally, the system-level performance of a boundary user is studied in terms of the coverage probability. The numerical results unveil that the SINR threshold, the separation distance, and the number of UAVs and their formations should be carefully selected to achieve the maximum coverage area inside and to reduce the unnecessary expansion outside the target area. Thus, this paper provides important design guidelines for the deployment of multiple UAVs in the presence of co-channel interference.

A QoS-Based Cross-Tier Cooperation Resource Allocation Scheme Over Ultra-Dense HetNets

An ultra-dense network (UDN) can increase the system throughput by deploying a mass of low-power nodes and can greatly increase the spectral efficiency and energy efficiency at local hot spots. However, due to the random deployment of a large number of base stations (BSs), severe inter-cell interference may occur, which hinders the development of resource allocation technology, especially on the computational complexity. In this paper, we propose a quality of service (QoS)-based cross-tier cooperation transmission scheme over the UDN. In order to mitigate the interference and improve the entire network throughput, a non-convex problem is formulated. To solve this problem, first, we define the cooperation signal-to-interference-plus-noise ratio (SINR) threshold that represents the ratio of transmission power of macro BS and SBS, and we utilize the stochastic geometry theory to analyze the effect of cooperation SINR threshold on the number of user equipment. Then, we use the dedicated channel to decrease the cross-tier interference according to the fractional frequency refused mechanism. To reduce the computational complexity, this resource allocation scheme is divided into two parts, i.e., subcarrier allocation and power allocation, and we also consider the QoS requirement. The simulation results verify that our proposed scheme has better performance than the other two existing algorithms while QoS is guaranteed.

Resource Allocation for D2D Communications Underlaying Cellular Networks Over Nakagami-<inline-formula> <tex-math notation="LaTeX">$m$ </tex-math> </inline-formula> Fading Channel

In this paper, we investigate the sum-rate maximization of cellular users (CUs) and device-to-device (D2D) pairs for the D2D communications underlaying cellular networks over the Nakagami-m fading channel. We consider a resource-abundant scenario where the number of CUs is more than that of D2D pairs and discuss the joint optimization of signal-to-interference-plus-noise ratio (SINR) thresholds and CU-D2D pairing. We formulate the problem as mixed-integer non-linear programming, which is NP-hard in general. To solve the problem, we propose a two-step approach. First, we add virtual D2D pairs to make the number of D2D pairs equal to that of CUs and derive the near-optimal SINR threshold for each possible CU-D2D pairing by the simulated annealing algorithm. Second, the optimal CU-D2D pairing can be obtained by the Hungarian (HG) algorithm. The simulation results show that: 1) the proposed SINR policy outperforms the other policies by about 11.3%-63.4% and 2) compared with several state-of-the-art resource allocation policies, HG allocation can achieve an average sum-rate improvement of 10.9%-72.8%.

A Stochastically Geometrical Poisson Point Process Approach for the Future 5G D2D Enabled Cooperative Cellular Network

Due to recent developments in the cellular communication system, stochastic process implementation is necessary. The cellular communication system exhibits random patterns in various domains, thereby compelling the utilization of stochastic processes to achieve an optimal output. User behaviors with respect to the variable geographical pattern, population density, architecture, data usage, and mobility over various cells are random in nature. Therefore, the stochastic-geometry-based Poisson point process (PPP) technique can be implemented to accurately analyze these random processes in device-to-device (D2D)-based cooperative cellular networks. The stochastic modeling entails the consideration of transmitters and receivers as the elements of stochastic point processes. The hexagonal method is not applicable for the implementation of heterogeneous network topologies, as it is not suitable for topologies, in which the cell size is not fixed. Therefore, a randomly designed heterogeneous network uses stochastic geometry as a viable solution for predicting the probabilistic parameters, including the cell interference, load distribution, coverage probability, base station (BS) mapping, and signal-to-interference-plus-noise ratio (SINR). Moreover, as a network architecture that is based on relay nodes (RNs), cellular and D2D users can be utilized in the domain of homogeneous random models. The associated phenomenon can be considered independent and Poisson. In this paper, the stochastic-geometric-based PPP approach is introduced for modeling the SINR, success probability, ergodic capacity, and outage probability for the D2D-enabled cooperative cellular network. The proposed PPP realistic model utilizes BS, RN, the cellular user (CU), and D2D user positioning method to design an interference-free network. The success probability, ergodic capacity, and outage probability for cellular and D2D users are used as metrics for evaluating the results with respect to various SINR threshold values and node densities. Moreover, the total success probability, ergodic capacity, and outage probability have been calculated for various multiple-input-multiple-output (MIMO) antenna configurations to validate the results. The results confirmed that the proposed PPP model approach outperforms the grid model and conventional multi-antenna ultra-dense network (UDN) approaches.

SINR and Throughput of Dense Cellular Networks With Stretched Exponential Path Loss

Distance-based attenuation is a critical aspect of wireless communications. As opposed to the ubiquitous power-law path loss model, this paper proposes a stretched exponential path loss model that is suitable for short-range communication. In this model, the signal power attenuates over a distance $r$ as $e^{-\alpha r^{\beta }}$ , where $\alpha$ and $\beta$ are tunable parameters. Using experimental propagation measurements, we show that the proposed model is accurate for short to moderate distances in the range $r \in ~(5,300)$ meters and so is a suitable model for dense and ultradense networks. We integrate this path loss model into a downlink cellular network with base stations modeled by a Poisson point process, and derive expressions for the coverage probability, potential throughput, and area spectral efficiency. Although the most general result for coverage probability has a double integral, several special cases are given, where the coverage probability has a compact or even closed form. We then show that the potential throughput is maximized for a particular BS density and then collapses to zero for high densities, assuming a fixed signal-to-interference-plus-noise ratio (SINR) threshold. We next prove that the area spectral efficiency, which assumes an adaptive SINR threshold, is nondecreasing with the BS density and converges to a constant for high densities.

Decoupled Access in HetNets With Backhaul Constrained Small Base Stations

This paper investigates the uplink (UL) and downlink decoupled access in heterogeneous networks with backhaul constraints. A capacity-based user association policy is proposed for users with decoupled access, where small base stations (SBSs) connect to macro base stations via non-ideal backhaul. The UL association probabilities are derived under this policy, where the limitations of association probabilities are obtained when the density of SBSs grows to infinity. Then, the UL signal-to-interference-plus-noise ratio (SINR) coverage probabilities are derived and analyzed for different SINR thresholds. According to the analysis, the effects of the limited backhaul capacity on the average UL SINR coverage probabilities are presented, where a jump discontinuity, which can be considered as a certain SINR threshold, is shown to be brought by the backhaul capacity constraint. It is demonstrated that denser deployment of SBSs helps improve UL performance significantly for users with SINR lower than such SINR threshold while hardly benefits those with SINR higher than it. Finally, the theoretical results are validated via simulations.

Stochastic Geometry Analysis of Downlink Spectral and Energy Efficiency in Ultradense Heterogeneous Cellular Networks

The energy efficiency (EE) is a key metric of ultradense heterogeneous cellular networks (HCNs). Earlier works on the EE analysis of ultradense HCNs by using the stochastic geometry tool only focused on the impact of the base station density ratio and ignored the function of different tiers. In this paper, a two-tier ultradense HCN with small-cell base stations (SBSs) and user equipments (UEs) densely deployed in a traditional macrocell network is considered. Firstly, the performance of the ultradense HCN in terms of the association probability, average link spectral efficiency (SE), average downlink throughput, and average EE is theoretically analyzed by using the stochastic geometry tool. Then, the problem of maximizing the average EE while meeting minimum requirements of the average link SE and average downlink throughput experienced by UEs in macrocell and small-cell tiers is formulated. As it is difficult to obtain the explicit expression of average EE, impacts of the SBS density ratio and signal-to-interference-plus-noise ratio (SINR) threshold on the network performance are investigated through numerical simulations. Simulation results validate the accuracy of theoretical results and demonstrate that the maximum value of average EE can be achieved by optimizing the SBS density ratio and the SINR threshold.

Coverage and Effective Capacity in Downlink MIMO Multicell Networks With Power Control: Stochastic Geometry Modelling

In this paper, coverage probability and effective capacity in downlink multiple-antenna cellular system are considered. Two scenarios are investigated; in the first scenario, it is assumed that the system employs distance-based fractional power control with no multicell coordination. For the second scenario, we assume the system implements multicell coordinated beamforming so as to cancel inter-cell interference. For both scenarios, the BSs are assumed to randomly uniformly distributed in the area according to Poisson point process. Using tools from stochastic geometry, tractable, analytical expressions for coverage probability and effective capacity are derived for both scenarios. Numerical results reveal that for a system with stringent delay quality of service (QoS) constraints, i.e. (traffic delay is intolerable), best performance can be achieved by suitably adopting fractional power strategy when transmitting to the users, while constant power allocation performs better than all other power allocation strategies when the delay QoS constraints get loose (tolerable delay). For coverage probability, a fractional power control is better than constant power and channel inversion power strategies for low signal-to-interference plus noise ratio (SINR) thresholds, while the constant power strategy performs better than others in high SINR thresholds.

Load-Dependent Handover Margin for Throughput Enhancement and Load Balancing in HetNets

Inbound handover (HO) or hand-in is done when the user equipment (UE) performs HO from a macrocell (MC) to a small cell (SC), while the outbound HO or handout is done when a UE hands over from SC to MC. On the other hand, the inter-SC HO is done when a UE performs HO between two SCs. The outbound HO is not as complex as the other two types, because the UE has only one HO target base station, i.e., the MC. Therefore, in this paper, we only consider the inbound and inter-SC HO types. The user may associate with a small cell for a very short time of stay (ToS), smaller than a short time of stay threshold, and this may cause frequently unnecessary HOs and result in service interruption causing degradation in the quality of service (QoS). In this paper, we propose a novel HO method for the purpose of load balancing and throughput improvement in heterogeneous networks (HetNets). The influence of interference from both MC and SC base stations is taken into account so as to offloaded the user from the congested cell and forced it to HO to the SC that gives a good data rate by choosing the best SC, which has the highest signal to interference plus noise ratio (SINR), from a reduced neighbor cell list (NCL). The NCL is optimized utilizing the SINR threshold and ToS. The proposed method utilizes a modified A3 HO initiation event taking into account the cell load and the interference. Results show that the proposed method can perform HO while maintaining the throughput to a good level. In addition, the proposed method has significantly reduced the inter-SC HOs and inbound HO and radio link failures compared to the existing methods. Under different network conditions, load factors, and call arrival rates, results show that the proposed method can give significantly better performance, thereby producing higher throughput for the user and the network.