Resource allocation trends for ultra dense networks in 5G and beyond networks: A classification and comprehensive survey

Carrier aggregation (CA) is a major feature in LTE-advanced technology that allows network provider to use more than one carrier simultaneously to increase capacity. CA uses two or more individual component carriers (CCs) of the same (intra-band) and different (inter-band) frequency bands. In this paper, we evaluate CA techniques with the test parameter using BLER and throughput inside the tested area of LTE network. The tested area is designed to represent most common environment in which LTE will be deployed. We use 30 MHz frequency bandwidth in the simulation to evaluate intra-band and inter-band CA technique performance. Two CCs is allocated for primary serving cell (PCell) and secondary serving cell (SCell). Simulation result shows for the downlink, BLER tend to increase, as the frequency configuration is increase. However, for the uplink BLER is zero. We found that for CA configuration with wider PCell bandwidth resulting better throughput. In CA intra-band, the throughput of non-contiguous CA is better than CA contiguous. Then in the inter-band CA, CC combination with a lower frequency produces higher throughput.

Carrier Aggregation Technique to Improve Capacity in LTE-Advanced Network

The embodiments of the present invention provide a method and a device for scheduling multi-service resources. The method comprises the steps of determining at least one user terminal within the coverage of base station equipment at the current moment; calculating the priority weighting factor of each user terminal at each component carrier; according to the service type of each user terminal and the priority weighting factor calculated through the above process, figuring out the resource scheduling priority of the user terminal on the resource block of each component carrier; according to the resource scheduling priority obtained through the above process, allocating corresponding resource blocks in respective component carriers to corresponding user terminals. The above priority weighting factor is composed of a location weighting factor and a carrier load weighting factor. The location weighting factor is influenced by the distance between the user terminal and the base station equipment. The carrier load weighting factor is influenced by the current load of the component carrier. According to the technical scheme of the invention, wireless spectrum resources are dynamically allocated, so that the resource allocation rationality is improved.

Method and device for scheduling multi-service resources

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, carrier's 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 user's 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.

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

The 5G LTE-Advanced with Carrier Aggregation (CA) technology is a promising next generation of all IP mobile networks which has been invented and developed by 3GPP. The CA technique is very vital to support the 5G LTE-A network with unprecedented speed of data transmission and minimal latency. One of the main challenges in the presence of CA is to offer robust and suitable resource scheduling scheme in order to support and fulfill the user level Quality-of-Services (QoS) requirements for diversified services “Real-Time (RT) and Non-Real-Time (NRT) traffic”. In this paper, a User-Level Quality of Service aware packet scheduling for OFDMA resource blocks in 5G LTE-A system with CA scheme is designed. An improved Joint User Carrier Scheduling algorithm (IJUCS) suitable to various traffic users is proposed by introducing the service weight factor. The design objective is to guarantee the user quality of service (QoS) and equitable allocation of radio resources among users. The simulation outcome demonstrates that proposed IJUCS has mitigate average packet delay, Packet Drop Rate (PDR), and variation of average packet drop (STD) of real-time users as compared to the conventional JUCS and fulfils the user's throughput requirements of NRT streaming video traffic.

An efficient scheduling scheme for heterogeneous services in OFDMA based 5G LTE-Advanced network with carrier aggregation

In this paper, we focus on the resource scheduling of Long Term Evolution - Advanced (LTE-A) with Carrier Aggregation (CA). Application of CA meets the demand of bandwidth in LTE-A by aggregating several discrete carriers together. With different fading characters, the aggregated carriers have different coverage between each other. Considering the backward compatibility, there exist both LTE-A and LTE users. In order to improve the performance of LTE users and cell edge users, an improved proportional fair (PF) scheduling algorithm suitble to multi-carrier system is proposed. In this algorithm, a variable to limit the number of carriers each user can access is set, and a carrier weight factor which is composed of carrier coverage weight factor and user category weight factor is introduced. Simulation results show that the proposed algorithm can effectively improve the performance of cell edge users and LTE users.

Qingliang Kong

Papers

A resource scheduling algorithm based on carrier weight in LTE-Advanced system with Carrier Aggregation