Long Term Evolution-Advanced Research Articles

Modified Best Channel Quality Indicator Scheduler for Heterogeneous LTE-A Network

In this paper, a Long-Term Evolution-Advanced (LTE-A) Modified Best Channel Quality Indicator (M-BCQI) Scheduler is proposed for enhanced cell edge throughput performance. The scheduling algorithm utilizes two time slots, each of 0.5 ms in length, with the First Time Slot (FTS) implemented with the Best Channel Quality Indicator (BCQI) algorithm has a CQI-focused Resource Block (RB) allocation mechanism, while the Robin (RR) algorithm is the mechanism used in the Second Time Slot (STS) for RB allocation. Vienna LTE system level simulator was used for the proposed scheduling algorithm assessment. The results obtained showed significant improvement, indicating 44% superior cell edge performance and 56 % better fairness index in comparison to BCQI. However, M-BCQI slightly underperformed by 4.2% in terms of average throughput in comparison to BCQI and by 7% in comparison to RR in terms of fairness index.

Power Optimization in a Multicell D2D Communication for Smart City in an mm-Wave Cellular Network: An mIoT Perspective

Device-to-device (D2D) communication ushers the realization of massive Internet of Things (mIoT) network for smart cities through long term evolution-advanced (LTE-A). In a multi-cell mm-Wave environment, acute interference from adjacent cells degrades the signal quality. Thus, our work focuses on the minimization of interference from the neighboring cells through optimal resource allocation and power optimization. Rate splitting multiple access (RSMA) technique is employed where the message to be transmitted is divided into two parts. Two modes for resource allocation are formulated which aims to maximize the throughput under certain interference constraints. Radius of coverage expression is derived for switching of modes to take place. Successive interference cancellation (SIC) is introduced as a power constraint which enhances the overall performance of the network. Subsequently, Lagrange’s dual optimization method is utilized for optimizing the D2D transmit power and also lowering the computational complexity of the overall network. Simulation results depict the overall performance efficiency in terms of transmission rate and signal strength. The results show that with the increase in difference of transmit power allocated to the common and private message, overall transmission rate also increases significantly. Finally, comparison with existing scheme validates the efficiency of the proposed work.

Energy efficient resource allocation algorithms combining PSO with FLC and Taguchi method in hybrid opportunistic networks

In order to reduce power consumption and delay time when mobile devices use wireless networks, this paper proposes dividing groups of mobile devices into clusters, and proposes two cluster architectures, which are dual-radio opportunistic networking for energy efficiency combining particle swarm optimization with fuzzy logic control and Taguchi by 2-hop of priority weighted round robin (DRONEE-PFT2-PWRR) and dual-radio opportunistic networking for energy efficiency combining particle swarm optimization with fuzzy logic control and Taguchi by multi-hop of priority weighted rate control (DRONEE-PFTM-PWRC). Furthermore, our proposed DRONEE-PFT2-PWRR algorithm increases cluster coverage using 2-hop and our proposed DRONEE-PFTM-PWRC algorithm improves power consumption of the system by multi-hop cluster architecture. Internal cluster communication uses Wi-Fi transmission packets, which can reduce energy consumption when a mobile device communicates with a long term evolution advanced (LTE-A) base station, and reduce interference on signals between mobile devices. In the selection of cluster heads, this paper uses particle swarm optimization (PSO) to find the best cluster head position, and the PSO fitness parameter value is adjusted using fuzzy logic control (FLC) combined with the Taguchi method. Priority weighted round robin (PWRR) architecture is proposed for LTE-A base station and cluster network resource allocation, and quality of service is introduced to give priority weight to packets according to data type. Furthermore, priority weighted rate control (PWRC) is proposed. This method determines whether the network resources of the base station meet the demands of the cluster, and then assigns weights according to the requirements of the cluster and its priorities, and finally allocates network resources according to those weights. This increases the uplink throughput of network resource allocation. Simulation results show that our proposed methods significantly outperform the DRONEE-weighted (DRONEE-W) algorithm method in terms of power consumption, network throughput, and transmission delay time.

Performance of LTE Advanced for Different Releases

Performance of LTE Advanced for Different Releases

Adaptive real-time spectrum selection framework and handover decision algorithm (RSSF-HDA) for heterogeneous networks

Carrier aggregation (CA) is a technology introduced by the Long-Term Evolution-Advanced (LTE-A) system to increase user throughput by combining a selected number of component carriers (CCs). Its integration with heterogeneous networks enables the mobile user equipment to take advantage of increased throughput and radio coverage of various access technologies. However, due to the mobility of user equipment, these innovations have increased the likelihood of handoff scenarios, resulting in a high outage probability and low throughput. Handover is a crucial part of mobility management since it enables users to move from one cell to another while maintaining connections. However, no single access technique can provide seamless communication without interruption or delay. As a result, creating a suitable handover decision algorithm is necessary for ensuring high-quality service continuity and dependable user equipment access to the network at all times. An Adaptive Real-Time Spectrum Selection Framework and Handover Decision Algorithm (RSSF-HDA) with optimal resource allocation to the deployed system model is presented in this paper. This effort is geared toward preventing communication failure and improving system performance. It further positions the 4G LTE-A framework for inclusive coexistence with the current 5G New Radio enhanced Mobile Broadband (eMBB) use case scenario. The results of the simulation reveal that this method increases system performance in terms of Cell edge spectral efficiency and Handover success rate above 10% and 13%, respectively, when compared to Conventional Handover Decision Algorithm (Conv-HDA) and Multi-Influence Factor Handover Decision Algorithms (MIF-HDA).

An overview of LTE/LTE‐A heterogeneous networks for 5G and beyond

AbstractThe potential of fifth‐generation (5G) and beyond wireless connectivity is to deliver higher data rates, much lower latency, more frequent increase in channel capacity, and significant improvements in Quality of Service (QoS), compared to the current Long Term Evolution (LTE) networks. The continued growth of smart devices, the introduction of trending multimedia applications, and the dramatic increase in demand and use of wireless data communication are already causing a significant load on current mobile networks. 5G wireless networks, with enhanced user data rates, delays, capacity and QoS, are anticipated to solve many of the existing problems of mobile networks. In this study, we review the emergent wireless LTE‐A and 5G networks to provide an overview of the challenges and the solutions suggested in recent literature towards forthcoming 6G networks. We first discuss the new structural changes associated with the Radio Access Network (RAN) design, heterogeneous network and LTE or LTE‐Advanced (LTE‐A) network. To understand the challenges and research gaps in 5G and beyond networks, the paper reviews the outstanding features of the new QoS and Self‐Organization Networks (SON) related to the emerging 5G networks. Data rates, bandwidth and coverage have been given significance throughout this review because these are some major challenges towards 6G networks. Since understanding the present state of 5G usage is critical to its adoption, the paper also discusses related field tests, trials, and simulation tests. Finally, we identify existing major research problems and outline potential research areas.

AN ENHANCED RESOURCE ALLOCATION SCHEME FOR LONG TERM EVOLUTION ADVANCED NETWORK

The emerging Long-Term Evolution Advanced (LTE-A) is an extended version of Long-Term Evolution (LTE) fourth-generation (4G) wireless broadband technologies that supports high speed transmission of multimedia applications, like video streaming, multimedia online game, Voice over IP (VoIP), browsing over the web etc. The Third Generation Partnership Project (3GPP) does not define a standard packet scheduling strategy in LTE-A. Therefore, it is expected for researchers and network service providers to design efficient schemes. This paper proposed an Enhanced Resource Allocation Scheme (E-RAS) that improves the packet scheduling strategy of LTE-A by addressing issues related to delay and fairness of users with both high and low channel conditions, for both Real Time (RT) and Non-Real Time (NRT) flows. The aim was achieved by using a fair spectrum allocation mechanism that consider the priority of RT flows of cell-centre users, without neglecting the throughput requirements of edge-centre users. Moreover, the proposed algorithm introduces an efficient traffic load balancing mechanism to efficiently regulate traffic load in LTE-A network. To evaluate the proposed scheme, simulation was conducted using the MATLAB programming with LTE-A system level simulator. The result obtained shows that the proposed scheme achieves better delay for RT and NRT traffics by 7% and 11% respectively as against the Resource Allocation Scheme to Optimize the Throughput (RASOT) scheme.

A random access channel resources allocation approach to control machine‐to‐machine communication congestion over LTE‐advanced networks

SummaryThe Internet of Things (IoT) is becoming a reality, and one of the core elements to make this reality come true is machine‐to‐machine (M2M) communication. With the fast‐growing rate in which devices are being deployed, communication among them has become crucial to support the development of IoT applications. The Long‐Term Evolution‐Advanced (LTE‐A) is a potential access network for these M2M devices. However, the LTE‐A inherited characteristics from older cellular network standards, which were designed for human‐to‐human (H2H) and human‐to‐machine (H2M) communication. Accordingly, supporting M2M communication poses some challenges to LTE‐A, with a highlight of the congestion and overload problems in the radio access network (RAN) during the random access channel (RACH) procedure. Such a problem arises due to the large number of devices sending access‐request messages to the network and the limited number of resources to satisfy this new demand. In this paper, we introduce a solution to mitigate the impact of M2M communication in the LTE‐A network. Precisely, we model how to divide the random access resources into different types of devices as a bankruptcy problem. Then, we propose two solutions: (i) A game theory approach to formulate the bankruptcy problem as a transferable utility game, and (ii) an axiomatic method where some elements are considered for judging the amount of resources each class should receive. The simulation results show that our approaches present improvements in terms of energy efficiency, impact control of M2M over H2H accesses, and priority respect among the different classes of devices.

Design and Optimization of Planar Inverted F Antenna (PIFA) for Wireless Applications

For 5G communication networks, including Long-Term Evolution Advanced mobile communication services, PIFA antenna is proposed. The proposed antenna structure is consisting of substrate, ground plane, shorting plate and feeding post connected to the ground plane. This antenna has been design based on a FR-4has relative permittivity of 4.3 it has a volume of (120601.5) mm3. The experimental results of the Planar Inverted F Antenna (PIFA) that have been measured at the range from (3-4 ) GHz of frequency experimentally using the Site Master (Anritsu S362E), it has been demonstrated that the return loss, bandwidth, VSWR, and impedance are −41.15dB, 510 MHz, 1.04and 48.414Ω respectively at resonant frequency 3.5GHz. The theoretical and practical values are so close to each other which justifies the antenna's excellent fit

Energy Efficiency In Optical-Wireless Access Network Using Dynamic Bandwidth Allocation

High capacity networks are needed for enormous quantity of internet traffic, which is driven by both the exponential growth of the number of people using the internet and the ongoing introduction of new high-bandwidth requiring applications. Combining optical and wireless technologies is a new and promising access network solution. The energy efficiency of telecommunication networks is therefore attracting increasing attention today than in the past. This study is aimed at evaluating energy efficiency of optical-wireless access network which combines Passive Optical Network (PON) and Long Term Evolution - Advanced (LTE-A) networks into one. The network was designed using Optimum Network Engineering Tool (OPNET) modeler software. Traffic was generated using inbuilt tools provided in the OPNET modeler software. Dynamic Bandwidth Allocation (DBA) algorithm was applied on the network and simulation was carried out using the simulation tool provided by OPNET to evaluate the effect of the DBA algorithm on the energy consumption and efficiency in the network. The findings showed energy utilization of 430 watt-second when DBA algorithm was applied on the access network as against 700 watt-second when it was not activated. This shows a 38.6% energy conservation. It was concluded that with the application of energy saving techniques to combined optical-wireless access network, substantial energy could be conserved even in the presence of heavy traffic without compromising the quality of service of the access network.

On the performance of multiple association with mobility support in 5G ultra‐dense networks: Realistic network simulation

AbstractA user equipment (UE) in ultra‐dense networks (UDN) has a high chance of being in close proximity to many cells. multiple association (MA) can be used to serve users with high data rate demands in such a deployment scenario. However, because of the small footprint of the low power node (LPN), mobile users may experience highly frequent cell re‐association issues. This paper focuses on solutions for UEs with high data rate demands as well as mobility management. User‐centric clustering, control, and user‐plane split usages are designed and investigated in coordination with the MA scheme. The clustering involves two stages: a master clustering and user‐centric clustering. This approach goes with mobility management in long term evolution advanced (LTE‐A)/fifth generation (5G) and can easily be integrated with the existing system. By setting some predefined threshold, the scheme attempts to treat UEs separately, based on their speed. In addition, a clustering approach was developed that generates virtual cells with which UEs are associated. The combination of MA with clustering and mobility support improves cooperation between the most appropriate cells to serve a specific UE. To validate the performance gains, synthetic system level and realistic network deployment simulations were used. The results show that the proposed scheme solves the frequent re‐association issues and improves the user throughput performance. In the realistic network evaluation, up to 65.7% decrease in re‐association frequency was obtained for the UEs average speed of 90 Km/h with cluster size . In addition, the percentile UE throughput when showed about 5.5% increase compared with the case when for pedestrian and low speed users.

Design of Semipersistent Resource Allocation in LTE-V Network

Radio network access technology currently used in 4G/5G is Long Term Evolution-Advanced (LTE-A), which was developed by 3rd Generation Partnership Project (3GPP). Device-to-device (D2D) communication is a technology enabling direct communications among wireless devices without forwarding through an evolved Node B (eNB). Moreover, D2D transmission can support vehicles as a vehicle-to-vehicle (V2V) environment. It is possible to avoid accidents via exchanging movement-related information among vehicles and effectively increase driving safety (and efficiency). However, radio resources are limited in radio networks. A vehicle transmits through D2D in Long Term Evolution-Vehicle (LTE-V) mode-3 standard, and an eNB can allocate the same spectrum radio resources for cellular and V2V links simultaneously. When using the same radio resources, the probability of interference may increase. This study designed a semipersistent resource allocation algorithm based on different cycles in an LTE-V network. Moreover, resource allocation under different cycles was analyzed, and a scheme for resource selection is proposed based on cycle size. The proposed Semi Persistent Gain Aware Resource Allocation (SP-GARA) scheme selects resources based on the expected sum rate of the cycle size and analyzes and discusses the results of the total sum rate at different cycles and speeds for an improved performance.

A Group Handover Scheme for Supporting Drone Services in IoT-Based 5G Network Architectures

Next generation mobile networks are expected to integrate multiple drones organized in Flying Ad Hoc Networks (FANETs) to support demanding and diverse services. The highly mobile drones should always be connected to the network in order to satisfy the strict requirements of upcoming applications. As the number of drones increases, they burden the network with the management of signaling and continuous monitoring of the drones during data transmission. Therefore, designing transmission mechanisms for fifth-generation (5G) drone-aided networks and using clustering algorithms for their grouping is of paramount importance. In this paper, a clustering and selection algorithm of the cluster head is proposed together with an efficient Group Handover (GHO) scheme that details how the respective Point of Access (PoA) groups will be clustered. Subsequently, for each cluster, the PoA elects a Cluster Head (CH), which is responsible for manipulating the mobility of the cluster by orchestrating the handover initiation (HO initiation), the network selection, and the handover execution (HO execution) processes. Moreover, the members of the cluster are informed about the impending HO from the CH. As a result, they establish new uplink and downlink communication channels to exchange data packets. In order to evaluate the proposed HO scheme, extensive simulations are carried out for a next-generation drone network architecture that supports Internet of Things (IoT) and multimedia services. This architecture relies on IEEE 802.11p Wireless Access for Vehicular Environment (WAVE) Road Side Units (RSUs) as well as Long-Term Evolution Advanced (LTE-A) and IEEE 802.16 Worldwide Interoperability for Microwave Access (WiMAX). Furthermore, the proposed scheme is also evaluated in a real-world scenario using a testbed deployed in a controlled laboratory environment. Both simulation and real-world experimental results verify that the proposed scheme outperforms existing HO algorithms.

TDM-PON and LTE-A Based Cost-Efficient FiWi Access Network Deployment

In recent times, usage of fixed wireless access (FWA) is gaining momentum even though fiber based existing services such as fiber-to-the-home (FTTH) are widely used for home Internet applications. We explore a time-division multiplexing passive optical network (TDM-PON) and long term evolution advanced (LTE-A) based cost-efficient access network planning strategy for combined usage of FWA and FTTH with the same network infrastructure. The proposed fiber-wireless (FiWi) access network satisfies all feasibility constraints and users’ quality of service (QoS) requirements. The proposed planning method judiciously identifies the network architecture and user service mode (FWA/FTTH).

QoS-based Packet Scheduling Algorithms for Heterogeneous LTE-Advanced Networks: Concepts and a Literature Survey

The number of LTE (Long-Term Evolution) users and their applications has increased significantly in the last decade, which increased the demand on the mobile network. LTE-Advanced (LTE-A) comes with many features that can support this increasing demand. LTE-A supports Heterogeneous Networks (HetNets) deployment, in which it consists of a mix of macro-cells, remote radio heads, and low power nodes such as Pico-cells, and Femto-cells. Embedding this mix of base-stations in a macro-cellular network allows for achieving significant gains in coverage, throughput and system capacity compared to the use of macrocells only. These base-stations can operate on the same wireless channel as the macro-cellular network, which will provide higher spatial reuse via cell splitting. Also, it allows network operators to support higher data traffic by offloading it to smaller cells, such as Femto-cells. Hence, it enables network operators to provide their growing number of users with the required Quality of Service (QoS) that meets with their service demands. In-order for the network operators to make the best out of the heterogeneous LTE-A network, they need to use QoS-based packet scheduling algorithms that can efficiently manage the spectrum resources in the HetNets deployment. In this paper, we survey Quality of Service (QoS) based packet scheduling algorithms that were proposed in the literature for the use of packet scheduling in Heterogeneous LTE-A Networks. We start by explaining the concepts of QoS in LTE, heterogeneous LTE-A networks, and how traffic is classified within a packet scheduling architecture for heterogeneous LTE-A networks. Then, by summarising the proposed QoS-based packet scheduling algorithms in the literature for Heterogeneous LTE-A Networks, and for Femtocells LTE-A Networks. And finally, we provide some concluding remarks in the last section.

Performance Analysis of Handover Initiation Parameters in Long Term Evaluation – Advanced (LTE-A) Network

In mobile network, mobility management plays an important role in order to support seamless handover in Long Term Evolution -Advanced (LTE-A) network. It is predicted that in the near future there will be an increase demand of voice and data traffic. Currently, LTE-A network purely depends on the hard handover that may cause disconnection to occur if the handover is not fast enough. When handover executes, it may experience failure because of the early handover, the late handover or handover to wrong cell. Thus, the cases of packet loss or communication interruption problems will occur. In this research, handover initiation parameters in LTE-A network is investigated. Firstly, a formulation of analytical framework has been developed to analyze the handover performance. Then, mathematical equations have been derived from the developed framework by incorporating the value of user’s speed and handover signaling delay parameters. Under this framework, the probabilities of handover failure were analyzed in order to observe the handover performance when the speed of user is increased. The numerical results show that if fixed value of Reference Signal Receive Power (RSRPth) is used, the number of handover failures increased as the speed increased. It also shows that it is essential to predict the handover signalling delay in advance to reduce the handover failure rate in LTE-A network.

Load Based Carrier Aggregation Algorithm for LTE Advanced

Long Term Evolution (LTE) supports transmission bandwidth upto 20MHz. Nowadays the multimedia rich applications connects billions of users worldwide. These services demands more number of Resource Blocks (RBs) to satisfy the Quality of Service (QoS) requirements and that can increase the data traffic in multifold. This crunch has led the Mobile Network Operators (MNOs) to increase the transmission bandwidth in order to fulfil the QoS requirements of the different services. In Release10, Third Generation Partnership Project (3GPP) provides a provision for MNOs to use Carrier Aggregation (CA) scheme in LTE-Advanced to aggregate upto five Components Carriers (CCs) of existing LTE carriers at the eNB to increase the transmission bandwidth upto 100MHz. Further, this scheme allows a User Equipment (UE) to transmit and receive data packets simultaneously on multiple CCs based on UE capability to meet the service requirements. However, the CC selection and efficient RBs utilization plays a vital role to optimize the system performance. Hence, in this paper using QualNet 8.2 network simulator the Load Based Carrier Aggregation Algorithm (LBCAA) is proposed for LTE-Advanced to aggregate the CCs of the existing LTE carriers at the eNB based on cell load in order to increase the transmission bandwidth to handle the data traffic growth. The simulations results illustrated that the proposed LBCAA for LTE-Advanced outperforms in the achieved average unicast received throughput, average unicast end-to-end delay and jitter as compared to LTE.

VaCoChain: Blockchain-Based 5G-Assisted UAV Vaccine Distribution Scheme for Future Pandemics.

This paper proposes a generic scheme VaCoChain, that fuses blockchain (BC) and unmanned aerial vehicles (UAVs) underlying fifth-generation (5G) communication services for timely vaccine distribution during novel coronavirus (COVID-19) and future pandemics. The scheme offers 5G-tactile internet (5G-TI) based services for UAV communication networks (UAVCN) monitored through ground controller stations (GCs). 5G-TI enabled UAVCN supports real-time dense connectivity at ultra-low round-trip time (RTT) latency of [Formula: see text] and high availability of 99.99999%. Thus, it can support resilient vaccine distributions in a phased manner at government-designated nodal centers (NCs) with reduced round trip delays from vaccine production warehouses (VPW). Further, UAVCNs ensure minimizes human intervention and controls vaccine health conditions due to shorter trip times. Once vaccines are supplied at NCs warehouses, then the BC ensures timestamped documentation of vaccinated persons with chronology, auditability, and transparency of supply-chain checkpoints from VPW to NCs. Through smart contracts (SCs), priority groups can be formed for vaccination based on age, healthcare workers, and general commodities. In the simulation, for UAV efficacy, we have compared the scheme against fourth-generation (4G)-assisted long term evolution-advanced (LTE-A), orthogonal frequency division multiplexing (OFDM) channels, and traditional logistics for round-trip time (RTT) latency, logistics, and communication costs. In the BC setup, we have compared the scheme against the existing 5G-TI delivery scheme (Gupta et al.) for processing latency, packet losses, and transaction time. For example, in communication costs, the proposed scheme achieves an average improvement of 9.13 for block meta-information. For 4000 transactions, the proposed scheme has a communication latency of 16 s compared to 36 s. The packet loss is significantly reduced to 2.5% using 5G-TI compared to 16% in 4G-LTE-A. The proposed scheme has a computation cost of 1.6 ms and a communication cost of 157 bytes, which indicates the scheme efficacy against conventional approaches.

Performance evaluation of the eICIC technique applied to a heterogeneous 4G mobile network

The evolution of LTE-A (Long Term Evolution -Advanced) has enabled the development of the Heterogeneous Network (HetNet) which uses multiple cell types due to the explosion in the number of connected subscribers. Different cell types of different sizes are deployed to share the load in the heterogeneous network. Unplanned deployment of small cells with low power, planning of the existing network, the power difference between cells; physical and meteorological phenomena affect the signal quality of radio links; crowded areas of metropolises with extremely high traffic hotspots force operators to increase the network capacity in a more economical way by installing small cells Several techniques have been developed in the literature. Among them, eICIC has emerged as the best and is used to overcome these interference problems in the heterogeneous 4G network. The performance evaluation of eICIC has been performed analytically and numerically in the time domain due to its use with the ABS (Almost Blank Subframe) of the OFDM system. The simulation areas are in center of the picocells, in the cell range extension (CRE) areas and in the macrocells. Analytically, we used the signal-to-interference-plus-noise ratio (SINR) to evaluate the bit rate, RSRP and RSRQ. The numerical method consists in proposing an algorithm for calculating the analytical parameters using Matlab software. The results obtained from the simulations are convincing and are not far from those obtained in the literature. The values obtained from the SINR correspond to the SINR-CQI table found in the literature. The throughput calculated in this work in relation to radio conditions (RSRP, RSRQ) reflects everyday realities.

Dual-spectrum resource allocation for coexisting LTE-advanced and Wi-Fi systems with imperfect channel state information

Long term evolution (LTE) and LTE-Advanced (LTE-A) based transmissions extended from licensed to unlicensed bands, known as LTE-unlicensed and licensed assisted access, can effectively alleviate the congestion of cellular bands. Efficient integration of the dual-spectrum in small-cells can further improve the achievable spectrum efficiency. In this paper, we optimize the power and resource allocation for LTE small-cells by jointly utilizing licensed and unlicensed bands, where practical issues like imperfect channel state information (CSI) and the characteristics of LTE unlicensed traffic are considered. More specifically, we formulate a stochastic mixed-integer non-linear programming (MINLP) problem to maximize the expected sum-rate (ESR) of the system. To solve this NP-hard problem, the so-called reduced-complexity joint licensed and unlicensed resource allocation (RC-JLURA) algorithm is proposed, where the original problem is transformed to a deterministic MINLP problem by employing an analytic approximation. Thanks to the Lagrange dual optimization based on a framework of alternate iteration, the proposed method can provide a near-optimum closed-form solution to the problem concerned, while maintaining a low computational complexity. The achievable performance of the LTE dual-spectrum mechanism is evaluated through simulations, which demonstrate the superiority of the proposed algorithm.