Saptarshi Chaudhuri

Utility based QoS aware uplink scheduler scheme for LTE Small Cell Network

LTE uses the SC-FDMA radio access technology for its uplink data traffic transmission from the User Equipment (UE) to eNodeB. To the best of our knowledge the uplink MAC scheduling decisions at the eNodeB that have been proposed so far for Small Cell network are mostly based on single parameters like channel awareness, buffer status, or minimal power transmission. In this paper, we propose a novel algorithm to support Quality of Service (QoS) aware uplink scheduling and resource allocation scheme at the small cell eNodeB. The proposed scheme dynamically calculates user weights through utility functions considering the parameters like queuing delay and throughput and does resource allocation based on uplink channel condition as well as Hybrid Automatic Repeat Request (HARQ) retransmission status.. The proposed scheduler is referred to as UQUS (Utility based QoS Uplink Scheduler).The performance of the proposed algorithm is compared with traditional scheduling algorithms such as round robin (RR) and proportionate fairness (PF). The simulation results show that the proposed UQUS mechanism achieves minimum gain of 4 times the video cell throughput and minimum gain of 2 times voip cell throughput compared with RR and PF schedulers.

Study of advanced-opportunistic proportionate fairness scheduler for LTE medium access control

Medium Access Control (MAC) scheduler entity forms one of the most important parts of any high speed packet access system like HSDPA or LTE. To the best of our knowledge the LTE MAC schedulers that had been proposed so far constitute of sub-carrier resource scheduling mostly based on single criteria like user throughput, link conditions, buffer constraints or power requirement. The above LTE MAC scheduler algorithms do not take care of users queue weight calculation taking all the above mentioned parameters into consideration. In this paper, we proposed a novel algorithm to support dynamic queue weight calculation and referred it as Advanced-Opportunistic Proportionate Fairness Scheduler for LTE (A-OPFS-LTE). The A-OPFS-LTE, calculates the queue weight based on multiple parameters like flow control feedback, hybrid automatic repeat request (HARQ) retransmission status, service class type, guaranteed bit rate, access terminal (ATs) channel condition, queues buffer utilization and later assigns the physical resource block. A-OPFS-LTE was able to schedule 14 uncompressed VoIP calls or 5 streaming type video calls every 1 milli-second scheduling cycle with packet loss less than 2%. Compared with MAC scheduler [10, 11], A-OPFS-LTE scheduler supports 10% cell throughput improvement and 30% more users

Opportunistic Proportionate Fairness Adaptive Scheduler for High Speed Packet Access System

3G MAC entity forms the most important part of any high speed packet access system. Due to high data rate requirements, MAC layer requires an efficient scheduler algorithm that can optimize the flow control, buffer utilization as well as channel quality requirements. The MAC entity consists of mainly the flow control engine, buffer management, scheduler and HARQ process that together provide a steady packet flow to the physical layer. In this paper, we propose a new algorithm to address the scheduler functionality. This algorithm provides the correct feedback to flow control and the HARQ process for data flow. The algorithm selects users for transmission bits based on their actual buffer occupancies per queue, dynamic token value traffic class priority, as well as channel conditions reporting from the access terminal. This algorithm is named as the opportunistic proportionate fairness scheduler (OPFS).

Maximizing spectral efficiency for cell edge users in LTE small cell network

Cellular communication systems especially LTE mandates the use of a simple and effective downlink power control of signals for controlling randomly dispersed users throughput, interference, connectivity link. Users at the cell edge experience low throughout due to packet retransmission, and packet drop scenario. Due to the above problems, the operator loses revenue from the cell edge users due to poor usage of the spectrum. In this paper we propose a novel downlink optimal power allocation scheme (DOPAS) which maintains a constant cell edge spectral efficiency of a LTE cell for a given user density distribution and traffic type. DOPAS can be used to enhance the cell edge throughput without compromising the throughput of the users present closer to the eNodeB. DOPAS uses the convex optimization method in allocating right power control for both cell edge and near cell users and thus guaranteeing cell edge spectral efficiency. The cell edge throughput using the proposed algorithm is compared against the homogenous power allocation scheme where the cell power is uniformly distributed across the resource blocks of the scheduled users. Results showed that using DOPAS, there is a significant rise in cell edge throughput as compared to the modified homogeneous power allocation scheme. The improvement varied from 20-80% depending on the number of users present in near cell and cell edge region resulting in maintaining an operator defined cell edge spectral efficiency.

A novel QoS aware medium access control scheduler for LTE-advanced network

Abstract LTE-A specification mandates Medium Access Control (MAC) scheduler entity to ensure strict guaranteed quality of service (QoS) both in downlink and uplink direction. To the best of our knowledge the LTE-A MAC schedulers proposed so far constitute of an objective function dependent on single constraints like number of radio resources, user throughput, user channel conditions, user data buffer or users downlink power requirement. In real world scenario if all the above constraints are not simultaneously taken into consideration, then it would be difficult to meet LTE-A QoS requirements. In this regard, to the best found knowledge, for first time in this paper, we propose a Multi Objective QoS aware LTE-A Downlink-MAC Scheduler (MOQDS) algorithm which adhere to two level QoS and fairness requirements of LTE-A specification. MOQDS algorithm does scheduling at two levels with each level has its objective function with its multiple operational constraints. Every transmission time interval, MOQDS uses multi-objective optimization to selects right user(s) and its corresponding application(s) to meet LTE-A QoS requirements. Simulation results are being compared with well referred LTE-A schedulers like modified largest weighted delay first, exponential rule proportional fairness and log rule under various ITU channel models. MOQDS achieves an average of 50% reduction in packet drop rate and minimum three times increased cell throughput as compared to above mentioned schedulers’ types and also with respect to all the other MAC schedulers mentioned in the references.

Self organizing method for handover performance optimization in LTE-advanced network

Abstract Classical wireless cellular networks configure semi-static values of handover decision parameters, which are usually been modified manually by the operator at a certain time interval post analyzing the network performance report. To reduce the operators manual intervention, 3rd Generation Partnership Project (3GPP) proposed Self-Organizing Network (SON) concept for Handover (HO) decision parameters optimization for the LTE-Advanced (LTE-A) network. However, considering high-speed mobility requirements and ever-growing complexity from the contemporary LTE-A network, neither the classical manual approach nor the existing SON based approach from the prior-art will be able to meet the stringent HO performance goal set by the standard. In addition, unconventional handover algorithms and their decision parameters setting can affect user throughput, increases call drops and finally degrades the mobility performance of the overall LTE-A network. Therefore, in this paper, we propose a novel and efficient self-optimizing HO detection along with HO execution and decision parameter optimization algorithm which is named as Handover Detection Self-Organizing-HO Parameters (HD-SOHP) based on Reinforcement Learning (RL) concept. HD-SOHP improves the users’ mobility performance by achieving effective session handovers thereby reducing call drop, HO failures and ping-pong at the cell level. Compared with the different SON based handover techniques as stated in Table 2, Table 3 and Table 4, HD-SOHP gives two times performance improvement with respect to call drop, handover failure and ping-pong for the users’ moving with speed up to 120kmph.

Downlink interference control through adaptive DRX in a carrier aggregation enabled LTE-Advanced heterogeneous networks

An LTE-Advanced (LTE-A) Heterogeneous Network (HetNet) constitutes of a macro cell and small cells, where, the former acts as an overlay network and the latter as an underlay network. In HetNet, enabling Carrier Aggregation (CA) usually results in severe downlink interference at small cells from macro cell because of high powered transmissions from macro cell on over-lapping component carriers (co-channels). The intensity of downlink interference is much more profound in HetNet enabled with CA than compared with a single carrier HetNet and ultimately affects the Quality of Service (QoS) of users connected to small cells. Some frequency domain solutions like cross carrier scheduling, soft frequency reuse, and downlink power control have been proposed so far, but they do not provide complete orthogonal transmissions among macro and small cells, leading to adjacent channel interference. Also, a few time domain approaches like Almost Blank Subframe (ABS), dynamic ABS have been proposed in the literature. However, the resource utilization of cells decreases due to high number of ABS assignments in the dense deployment, which also results in low user throughput. In this paper, we propose a combined time domain and frequency domain novel idea for downlink interference control, which is via adaptive Discontinuous Reception (DRX) settings through Multi-Objective optimizations and an optimal carrier allocation scheme, respectively. The proposed idea mitigates the downlink co-channel interference by enabling intermittent data reception at the User Equipment (UE) through adaptive DRX settings, also it utilizes an effective carrier allocation scheme such that users are always allocated to carriers with least interference. The analytical model and simulation results reveal that the proposed idea achieves average gain of 3.5 times w.r.t cell throughput when compared with well-known downlink interference mitigation schemes.

A dynamic scheme for user load balancing in a multi-carrier LTE-Advanced network

To achieve ever increasing demand for higher user throughput, 3rd Generation Partnership Project (3GPP) have introduced Carrier Aggregation (CA) feature in the Long-Term Evolution — Advanced (LTE-A) standard. Wherein, the CA feature widens the transmission bandwidth by aggregating multiple Component Carriers (CCs) to meet the demand for higher data rate. To the best of our knowledge, till now available literatures have not addressed the challenges related to presence of multiple carriers in a base station system which usually results in the problem of user load imbalance among carriers due to improper and static user load assignment across CCs. In this paper, to solve the above challenges, we present a Dynamic and Optimal CC Load Balancing Scheme (DOCC-LBS) for user assignment across CCs via Multi-Objective Optimizations in which both, core network traffic load and channel quality conditions of CC are taken into account. The proposed novel dynamic load balancing scheme effectively balances the user load across CCs while achieving high user throughput. The analytical model and simulation results reveal that under the proposed mechanism the average user throughput doubles when compared with existing load balancing schemes such as Round Robin (RR) and Maximum Component Carrier to Interference (MCCI).

QoS aware downlink scheduler for a carrier aggregation LTE-Advance network with efficient carrier power control

Carrier Aggregation (CA) features will enhance Quality of Service (QoS) for the users as well as cell throughput of the LTE-Advanced (LTE-A) base-station (eNodeB). To deliver a high QoS for users, an eNodeB requires a well-designed and efficient CA enabled downlink scheduling algorithm. Enabling aggregation of multiple component carriers leads to huge power consumption compared with non-CA scenario. To the best of our knowledge, CA enabled downlink scheduling mechanisms which have been proposed so far in the literature has not addressed simultaneously the QoS, carriers power allocation and Physical Resource Block (PRB) utilization while taking scheduling decisions. In this paper, we propose a novel and efficient Multi Objective based CA Scheduling (MOCAS) algorithm, namely MOCAS-MinMax and MOCAS-NSGAII (Non-Dominated Sorting Genetic II). Analysis as well as simulation results reveal that for 100 cell users scenario, MOCAS (MinMax and NSGAII) gives a minimum cell throughput gain of two times compared with well-referred CA schedulers like round robin (RR), Efficient Packet Scheduling (EPS), Joint Carrier Scheduler (JS), SJS-PF, Cross-CC User Migration (CUM). Moreover, MOCAS have higher PRB utilization as well scheduling energy efficiency compared with RR and EPS.

Design of adaptive MAC for high speed packet access system

Medium Access Control (MAC) entity forms the most important part of any high speed packet access system. Complying with the high data rate requirements, MAC Layer requires a highly efficient Scheduler algorithm working in tandem with the Flow Control, buffer utilization , access terminalpsilas capability and with Channel Quality requirements. The MAC entity mainly consists of the Flow Control Engine, Buffer Management, Scheduler , Encoder and HARQ process that together provide a steady packet flow to the physical layer. In this paper, we study the new design methodology for MAC layerpsilas based on the modified Opportunistic Proportionate Fairness Scheduler (OPFS)12 algorithm which dynamically adapts the Transport Format (TF) Selection either based on legacy algorithm or access terminalpsilas feedback taking stress condition in the system, balancing Proportionate and Priority factor dynamically per scheduling cycle , providing the correct feedback to Flow Control and the HARQ retransmission process. MAC calculates the weighted capability per queue per user depending on the retransmission, actual buffer occupancies, dynamic token value , Traffic Class Priority, as well as in varying channel conditions and sends the selected queue to the physical layer.