An efficient downlink packet scheduling algorithm in LTE-Advanced systems with Carrier Aggregation

Carrier Aggregation (CA), which is a method that aggregates multiple Component Carriers (CCs) of the same or different frequency bands, is one of the Long Term Evolution-Advanced (LTE-Advanced) key features. It allows the LTE-Advanced to support wider transmission bandwidth. Another important requirement is that the system needs to support a mixture of LTE-Advanced and the legacy Long Term Evolution (LTE) users simultaneously. The LTE-Advanced users can transmit packets on all of the available CCs whereas the LTE users are limited to transmit packets on a single CC. At the early stage of migration, there will be many LTE users in the LTE-Advanced system. Therefore, CC selection algorithm that is responsible to assign a CC to each newly-arrived legacy LTE users is becoming of paramount importance in the LTE-Advanced system. The existing CC selection algorithms can slightly provide good mobile cellular performance in terms of maximizing the throughput and balancing the load. To further improve the LTE-Advanced performance, this paper proposes a novel CC selection algorithm that takes the channel quality and traffic load in each CC into consideration. It was shown via simulation that the proposed algorithm can significantly improve the downlink LTE-Advanced performance as compared to the conventional CC selection algorithms.

In order to achieve up to 1 Gbit/s peak data rate in the future IMT-Advanced mobile systems, carrier aggregation (CA) technique is introduced by the 3GPP to support higher data rate transmissions over wide frequency bandwidths (up to 100 MHz) in the LTE-Advanced (LTE-A) standards. This technical envisagement puts forward the new challenge in resource allocation. In this paper, we investigates the component carrier (CC) allocation in LTE-A system. We first separate the resource allocation into CC-, resource block (RB)- and power-allocation. Then, an optimization problem that maximizes system sum capacity with proportional fairness(PF) guarantee is formulated. To simplify the optimization problem, we present an approximate RB allocation approach and two alternative objective functions. A greedy algorithm for CC allocation (GACCA) with low computational complexity is presented to solve the simplified optimization problem. To further improve the quality of solution, we introduce cross entropy method into GACCA. Numerical simulations verify the efficiency of the proposed algorithm.

Component carriers (CCs) in a Long Term Evolution - Advanced (LTE-A) system are limited by maximum 100 radio bearers (RBs) on a 20 MHz CC due to a fixed 15 KHz subcarrier bandwidth. However it is able to be changed in the future, so that a study regarding heterogeneous CCs which have diverse RBs above 100 on a CC is needed at this moment. To support non-contiguous carrier aggregation (CA) with the these conditions, a heterogeneous joint CC packet scheduling algorithm interacting with a radio resource control (RRC) is considered in this paper. The performance of the joint CC packet scheduling algorithm on heterogeneous CCs with different channel characteristics has been analyzed and compared through computer simulations as well. According to the results, we found that an 800 MHz CC exhibits approximately 4 dB better channel gains than a 2.1 GHz CC. We also obtained a capacity increase of about 15-40% for a joint CC maximum rate (MR) algorithm and about 2-28 % for a joint CC proportional fair (PF) algorithm when the number of users is increased. On the other hand, in a round-robin (RR) scenario, we were unable to notice any differences between the independent CC and joint CC packet scheduling policies. Furthermore, looking at the impacts of different amounts of RBs on 800 MHz + 2.1 GHz CCs, we can conclude that a one-to-one RB ratio with respect to the MR, PF, and RR algorithms has a better performance compared to other cases, and thus, owing to the better channel gain, the smaller the RBs of the 800 MHz CC, the better the performance achieved.

Carrier aggregation (CA) is a good solution for third-generation (3G) Long Term Evolution-Advanced (LTE-A) systems to fulfil the system bandwidth (BW) extension requirements and also ensure the backwards compatibility towards 3G LTE. In this paper, we compare the quality of service (QoS) performances of two different multi-user scheduling schemes in CA based LTE-A systems, i.e. separated random user scheduling (SRUS) and joint user scheduling (JUS). The former is simpler but less efficient while the latter is optimal but with higher signalling overhead. Moreover, only one single component carrier (CC) is needed to access for user equipment (UE) in the case of SRUS while all the CCs have to be connected in the case of JUS. Simulation results show that the SRUS scheme is feasible and only little performance loss in continuous and heavy traffic load scenarios with full or Poisson-based finite buffer traffic input.

By aggregating Component Carriers (CCs) to enlarge the transmission bandwidth, Carrier Aggregation (CA) greatly improves the peak data rate for Long Term Evolution-Advanced (LTE-Advanced) system. However, more than one carrier scheduling in a system results in the problem of load imbalance among carriers. This paper presents a UE-grouping based load balancing (UGLB) scheme for CC scheduling in which both the load and channel quality conditions of CC are taken into account and different condition settings are provided to different UE groups. The proposed scheme not only properly balances the load among CCs but also achieves high throughput. Through simulation the performance of UGLB scheme is verified.

The link performance between base station (BS) and user equipment (UE) in long term evolution-advanced (LTE-A) system is already quite close to the Shannon limits and from a pure link-budget perspective, the highest data rates supported by LTE-A require a relatively high signal-to-noise ratio. In later releases of LTE-A, various tools such as relaying, enhancing the support for low-power BSs and improving the link budget are included. This paper studies the relay stations (RSs) for LTE-A downlink physical layer. Multi-input multi-output amplify-and-forward RS is used to enhance the received signal of UEs at cell edge. This paper proposes RSs with orthogonal space–time block codes (OSTBC) transmission for LTE-A system. The received signals for different UEs scenarios are mathematically derived and analyzed. The symbol error rate performance of proposed LTE-A system is illustrated for the scenarios of UEs. Results show that the proposed LTE-A system based RSs with OSTBC transmission improve link performance and achieve higher diversity gains.

This paper investigates user pairing algorithm in multiple-user multi-input multi-output (MU-MIMO) systems. Considering that users report Precoding Matrix Index (PMI) and Rank Indicator (RI) to indicate precoding matrix, multiple orthogonal PMI&RI clusters are designed to reduce the MU-channel state indicator (MU-CSI) feedback overhead. On the basis of such predefined orthogonal clusters, a novel user pairing algorithm is proposed to make the tradeoff between cell throughput and MU-CSI feedback overhead. To further simplify computational complexity, we propose a suboptimal algorithm. Unlike previous researches, the transmission data streams of paired users are adaptively adjusted according to the channel condition. Simulation results show that the cell throughput gain achieved by our proposed algorithms is close to that achieved by other user pairing algorithms, with less feedback overhead in Long Term Evolution-Advanced (LTE-A) systems.

With the increasing mobile traffic demands generated inside building, indoor relay is proposed for solving indoor dead spot and hot spot scenarios. This paper focuses on opportunistic spectrum sharing among indoor users (UEs) and outdoor users in the long term evolution-advanced (LTE-A) system without introduce significant interference to the primary transmissions. Three intelligent sharing schemes including indoor UEs sharing outdoor spectrum, indoor UEs inside different in-building coverage areas sharing spectrum with each other and outdoor UEs sharing indoor spectrum are proposed. Simulation results show that both indoor and outdoor uplink throughputs are tremendously improved compared to the no spectrum sharing scheme.

Multi-input-multi-output (MIMO) systems along with orthogonal frequency division multiplexing (OFDM) technique plays a crucial role in 4G based wireless networks. The inclusion of MIMO technology enables new types of links such as downlink multi-user communication. Long term evolution (LTE) systems are based on multi-user MIMO technologies, which have flexible bandwidths. In this paper, we derived closed form expression of bit error rate (BER) for multi-user LTE and LTE-Advanced (LTE-A) systems. Moment generating function (MGF) and pair-wise error probability (PEP) based approaches are used to derive these BER expressions. Theoretical results of BER are validated using simulation results for different number of users. Results are plotted on the basis of various features such as coordinated multipoint (CoMP) transmission and reception, multimedia broadcast and multicast services (MBMS) and allocation of Bandwidth in LTE and LTE-A systems.

The deployment of small cells with carrier aggregation (CA) technique is a significant feature of next-generation cellular networks. The potential benefits of dense base stations (BSs) deployment are provided by using proper interference management mechanisms. Meanwhile, the user equipments (UEs) can simultaneously access multiple component carriers (CCs) to meet the dramatically increased traffic demand by means of CA. In this paper, an optimization problem consists of UE-BS association, CC configuration, frequency resources scheduling, and power allocation with adaptive modulation schemes is investigated to enhance energy efficiency, focusing on the quality of service (QoS)-aware CA. To obtain the near optimal solutions as well as the consideration of computational complexity, a cross entropy- based algorithm (CEA) is proposed to jointly solve the combinatorial problem. Compared to the traditional heuristic algorithms, the merits of proposed scheme can be observed via simulation results.

The advancement in technology and smart gadgets have led to the demand for more data and higher data rates. Despite efficient use of spectrum, it is not able to achieve the data rate of 1 Gbps as required by Long Term Evolution Advanced (LTE-A). To achieve such a high data rate, this requires a higher transmission bandwidth which cannot be achieved by a single carrier. So, a new technique is introduced called carrier aggregation to aggregate two or more component carriers to achieve higher bandwidth. The carriers that are to be aggregated can be from continuous spectrum and can also be from different bands which result in three types of carrier aggregation, i.e., intra-band contiguous, intra-band noncontiguous, and inter-band carrier aggregation. The most important feature to move from LTE to LTE-A is carrier aggregation and the main advantage of this is that it is backward compatible. As per 3GPP release it is given that up to five component carriers can be aggregated to achieve a bandwidth of 100 MHz. Thus, in this paper the carrier aggregation up to three-component carriers by taking different number of downlink resource block for each aggregated carrier and comparative study of increment in the bandwidth will be carried out and the simulation results the enhancement of bandwidth using carrier aggregation.

Small cells are low power nodes, which have lower transmit power than the macro eNodeB. They are regarded as one of the important solutions in long term evolution advanced (LTE-A) to deal with the dramatically increased mobile data traffic. Small cells deployments in LTE-A release 12 with 4 small cells in a cluster suffer from stronger inter-cell interference than heterogeneous network (HetNet) in the previous release of LTE-A, where one small cell exists in a cluster. We investigate the joint least squares channel estimation (JLSCE) over demodulation reference signals (DMRS) spreading in time and frequency resources in LTE-A systems. Furthermore, different receiver structures using least square channel estimation (LSCE) and JLSCE are investigated in small cell deployments with the presence of strong inter-cell interference. Our results show the linear minimum mean square error (LMMSE)-interference rejection combining (IRC) with LSCE is the most efficient receiver structure compared to the enhanced (e)LMMSE-IRC with JLSCE, interference cancellation (IC) with eLMMSE-IRC and maximum ratio combining (MRC) receiver structures for signal detection in small cell deployments.

In Long Term Evolution Advanced (LTE-A) several new features have been added to deal with the ever-increasing demands for higher data rates and spectral efficiency. One of the key features that the Third Generation Partnership Project (3GPP) has introduced is the Relay Node (RN), a low power low cost device used to increase the spectral efficiency, especially at the cell edge. In this paper, we propose to use RNs to address a challenging new problem emerging on the horizon: the expected tsunami of Machine-to-Machine (M2M) traffic in cellular and mobile networks (in LTE, and LTE-A). By taking advantage of RN’s low cost, low power, and small size we outline the challenges of and one possible design for using RNs to integrate M2M traffic in LTE-A. To the best of our knowledge, this is a novel idea that has not yet been proposed and may give RNs more longevity and therefore greater value.

Long Term Evolution (LTE) Networks are being planned to be upgraded to LTE Advanced along with increasing availability of Release 10 User Equipment (UEs) and Spectrum Availability for Carrier Aggregation. LTE Advanced brings a major step increase in Down Link and Uplink Throughputs and related spectral efficiencies. This paper explains the evolution of Frequency Division Duplex (FDD) throughputs for different Channel Bandwidths. The maximum theoretical physical layer throughputs and expected actual application layer throughputs after removing the necessary overheads by different broadcast, signaling, synchronization & random access channels have been explained with an impact analysis thereof. Throughput gains for upcoming LTE Advanced deployments have been computed for Frame Structure Type 1 (FDD) for Channel Bandwidth of 1.4 MHz, 3MHz, 5 MHz, 10 MHz, 15 MHz and 20 MHz along with Carrier Aggregation of 2 & 5 Component Carriers. Impact of increasing Signaling Channels, retransmissions & code rate on throughputs has been explained so that the computations can be extended to any deployment scenario.

Carrier aggregation (CA) is a technology first introduced in LTE-Advanced (LTE-A) to increase the peak data rate of 4G networks (for example, the maximum available speed) [1]. The mobile network operator can increase the total available bandwidth for a single user by aggregating multiple channels together, thereby increasing the user data rate as well as the spectrum utilization efficiency and resource allocation flexibility of the entire network. Before LTE-A, mobile network operators could allocate the spectral resource only to a particular user within a single designated frequency band, limiting the maximum channel capacity. The realization of CA allows network operators to create larger channels from nonadjacent spectrum blocks. For example, operators can use a 10-MHz carrier from the 2,100-MHz band and combine it with another 5-MHz carrier from the 700-MHz band to create a 15-MHz LTE channel. The LTE-A standard specifies that each of the component carriers (CCs) of the communication signal is limited to 20 MHz of bandwidth. Aggregation of up to five CCs allows a maximum of 100 MHz of total signal bandwidth, as depicted in Figure 1. This leads to a fivefold increase in channel capacity and data speed [2]. It is projected that CA technology will continue to be widely and intensively used in future-generation communications, such as 5G.