Heterogeneity is defined as one of the core merits in the 5th Generation (5G) mobile systems. Such a trait is prominent in modern 5G traffic scenarios, i.e., enhanced Mobile Broadband (eMBB), where coarse Quality of Service (QoS) profiles need to be satisfied over the shared transmission channel. For that, Radio Resource Management (RRM) became a challenging problem that should be figured out based on the traffic scenario. Extensive efforts dwelled in the literature attempt to solve the resource allocation problem in the downlink channel by maximizing the gain for a certain aspect in the QoS profile. This, however, poses a challenge for 5G-related traffic scenarios such that multi-dimension QoS shall be attainable. Therefore, in this paper, a Delay-aware Resource Allocation for Guaranteed Fairness and minimal Loss (DRAGFL) is proposed to enhance the QoS for Real-Time (RT) services in eMBB 5G Heterogeneous Networks. The ultimate objective of DRAGFL is to maintain a steadily low latency for delay-sensitive flows without restraining the service fairness and the data loss in the overload states. DRAGFL enhances the efficiency of the MAC layer scheduler throughout three phases. Firstly, generating delay-derived weight matrix of the resources blocks to radio bearers from eMBB different classes. Then, greedy-based flows prioritization for Resource Blocks (RBs) assignment. Finally, the data rate of the RT and Non RT (NRT) flows is further emphasized through a channel-aware principle that is invoked conditioning to the remaining radio resources and available data to be scheduled in the interval. The performance evaluation using system-level simulations reveals prominent gains of DRAGFL in sustaining a steadily low end-to-end delay in the high congestion states. Moreover, it maintains ideal states of service fairness with low data loss for different traffic loads to indicate a promising MAC scheduler for the developing scenarios of 5G.

Guaranteeing Quality of Service (QoS) for heterogeneous traffic is a major challenge in the Fourth Generation (4G) mobile networks. Therein, the absence of sophisticated resources allocation process at the base station jeopardizes QoS in terms of latency data transfer. It has been observed from the literature that low delay bounds might be ensured, however, at the expense of other QoS aspects; for example, throughput and data loss. Therefore, in this article, we propose an effective Delay–based and QoS–Aware Scheduling (DQAS) scheme with a low complexity overhead as an efficient solution for the resource allocation issue in LTE Medium Access Control (MAC) layer. The ultimate aim of DQAS is to minimize delay for Real-Time (RT) traffic while still offering a good level of QoS. Complying with QoS of different traffic types, we effectively analyze the queue buffer of each user flow by developing an algorithm called Efficient Delay Control (EDC) that weights each flow priority in terms of delay. Then, this weight is utilized as a principle for the scheduling decision on the attending flows. Furthermore, the Least Delay Increase (LDI) algorithm is developed to tune the scheduler behavior to maintain a balance between delay and system throughput. Simulation results considering different user mobility levels reveal that DQAS significantly guarantees a low end-to-end delay trend that is independent of increased RT load, and moreover, a reasonable throughput and data drop levels compared to other existing schedulers.

It is axiomatic that providing more transmission power by the cell, returns high data rates; but in contrary, more power is consumed which leads to energy exhaustion. The Quality of Service (QoS) in long term evolution urban macrocell networks gives a high concern to green communication by wisely utilizing the limited cell power to improve network performance. Nevertheless, in conventional schemes, it is observed that the maximum power assigned to the evolved Node B (eNB) is fully utilized each time transmission interval regardless the transmitted amount of data. Consequently, a high level of power dissipation commonly occurs at the eNB that is caused by either an unused allocated power or an excessive subchannel power allocation which is beyond the required portion for data blocks transmission. Therefore, in this paper, we propose an efficient scheme, namely link adaptive power control and allocation (LaPCA) to mitigate the overused transmission power of the cell, and thereby, enhancing system energy efficiency while maintaining a good QoS level. The main principle in LaPCA is to control the portion of cell transmission power to be proportional to the volume of data flows that are nominated for transmission during the scheduling process. This power is then distributed over the allocated subchannels by means of nonconvex optimization to enhance system performance. System-level simulations reveal that LaPCA achieves an outstanding energy efficiency and maintains an increased throughput level and low loss ratio as more traffic load is offered to the network.

The steady growing trend of user demand in using various 4G mobile broadband applications obligates telecom operators to thoroughly plan a precise Quality of Service (QoS) contract with its subscribers. This directly reveals a challenge in figuring out a sophisticated behavior of radio resources (RBs) at the base station to effectively handle the oscillated loads to fulfill their QoS profiles. This paper elaborates on the above issue by analyzing the behavior of the downlink packet scheduling scheme and proposes a solution to bridge between the two major QoS indicators for Real-Time (RT) services, that are, throughput and delay. The proposed scheduling scheme emphasizes that a prior RBs planning indeed has an immense impact on the behavior of the deployed scheduling rule, particularly, when heterogeneous flows share the channel capacity. System-level simulations are performed to evaluate the proposed scheduling scheme in a comparative manner. The numerical results of throughput and delay assured that diverse QoS profiles can be satisfied in case of considering RBs planning.