Proportional Fairness Research Articles

Maximum-Largest Weighted Delay First Algorithm for Heterogeneous Traffic in 4G Networks

Real time applications with strict QoS like delay sensitive applications require an advanced technology to adopt them. This is where Long Term Evolution-Advanced (LTE-A) fulfills this requirement. With this ever evolving technology the need for improvements is required. Packet scheduling is one of the important key features of LTE-A, where it dictates user selection and transmission of those user’s packets based on the priority of the users to reach the receiver correctly. Packet scheduling is one mean to achieve those QoS requirements that real-time applications require. Such algorithms are HARQ Aware Scheduling Algorithm (HAS), Retransmission Aware Proportional Fair Algorithm (RAPF), Chase Combining Based Max C/I Scheduling and Maximum- Largest WeightedDealy First algorithm (M-LWDF). In this paper, M-LWDF is one of the best algorithms in LTE-A which was chosen for further investigated to support QoS in high mobility environment. Packet Loss Ratio (PLR), and Mean User Throughput performance measures were used to validate the performance of M-LWDF algorithm against other algorithms using similar mobile environment. Simulation results indicate the capability of M-LWDF algorithm within the threshold of the performance measures against other benchmarks where it has demonstrated more efficiency to support and improve the performance of real-time multimedia traffic.

An axiomatic characterization of fairness in transport networks: Application to road pricing and spatial equity

This paper considers the important issue of fairness in transportation. Designing fair policies in transportation is critical since transport networks are generally recognized as public goods. Moreover, the effects of road pricing may be significantly different for travellers from different geographical regions. Hence, any revenue collected from road pricing or infrastructure funding policies ought to be appropriately redistributed among the population of different geographical regions. In this work, we focus on spatial equity in the road pricing revenue assignment problem. We examine well-known fairness schemes commonly discussed in the literature: opportunity fairness, proportional fairness (individual value and marginal value), and market fairness. We conduct an axiomatic characterization of these schemes to demonstrate their properties and highlight their policy implications. We then present a practical implementation of the proposed fair pricing revenue assignment mechanisms on Winnipeg's downtown network. The results reveal that market fairness is the most axiomatically restrictive scheme and that this scheme is related to individual value and proportional value proportional fairness under specific conditions. We also demonstrate a paradoxical situation where a market or marginal value proportional fair assignment requires a certain group to pay taxes, because they receive more benefits than other groups. In turn, opportunity fairness is shown to be the least restrictive revenue assignment scheme and to require minimal computational resources.

Mode selection considering fairness in D2D‐enabled cellular networks

AbstractIn this paper, we consider the problem of mode selection, resource allocation, and power control for device‐to‐device (D2D) communications in cellular networks. We propose optimization frameworks based on max‐min fairness and proportional fairness where cellular and D2D links share the cellular resources. The optimization problem is solved in different resource sharing modes (ie, cellular, overlay, and underlay), and the mode leading to the highest optimal value is selected in the system. We further propose a two‐stage mode selection scheme based on channel quality in which the resource partitioning is expressed in closed form. We compare the performance of the proposed schemes with that of optimization framework based on sum‐rate and no‐mode selection scheme. The numerical results indicate that cellular and D2D links achieve higher rates in proportional fairness and max‐min fairness schemes compared to no‐mode selection scheme. While the rate improvement of D2D link is more significant in sum‐rate optimization, the cellular link may achieve lower rate in this scheme compared to other methods including the no‐mode selection scheme. The results also reveal that the rates of cellular and D2D links in channel quality scheme can vary within the range of rates obtained in max‐min and sum‐rate optimization frameworks.

A Resource Allocation Scheme with Fractional Frequency Reuse in Multi-cell OFDMA Systems

In this paper, a resource allocation scheme is proposed for multi-cell OFDMA systems in downlink under the fractional frequency reuse environments. The objective considers balancing between the maximization of the system throughput and the satisfaction of the user’s data rate requirement. Due to the severe co-channel interference for cellular networks with full frequency reuse, a dynamic fractional frequency reuse scheme is adopted in the cellular network which divides all subcarriers in each cell into two groups: a super group and a regular group. The dynamic fractional frequency reuse scheme can guarantee the intra-cell orthogonality and reduce the inter-cell interference. Therefore, the procedure of the proposed resource allocation scheme includes two main parts: frequency partition and subcarrier allocation. First, each subcarrier is assigned to either the super group or the regular group based on designed functions in all cells. Second, we allocate subcarriers to users by utilizing the designed functions. The designed functions are developed based on the proportional fairness scheduling, the logarithm transformation, and the Lagrangian technique. The designed function is coupled with the instantaneous data rate, the average data rate, and the data rate requirement. Simulation results show that the proposed scheme provides a higher system throughput and improves the outage probability compared with existing schemes.

Adaptive Control of CRE with Proportional Fair Resource Scheduling in LTE HetNets

Adaptive Control of CRE with Proportional Fair Resource Scheduling in LTE HetNets

Energy-Efficient Joint User Association and Power Allocation in Relay-Aided Massive MIMO Systems

Energy efficiency is an important metric for downlink transmission in an amplify-and-forward relayaided massive multiple-input multiple-output system, but has not been well investigated. In this work, considering the characteristics of such a system and quality-of-service requirements of users, the energy-efficient joint user association and power allocation problem is studied. First, the closed-form expression of system energy efficiency under the proportional fairness criterion is derived. Then, the proportionally fair utility of system energy efficiency is maximized under constraints of minimum signal-to-noise ratio requirements of users and maximum transmit powers of the base station (BS) and relay stations. As it is difficult to solve this optimization problem directly due to its mixed-integer and non-convex features, the original problem is decomposed into a user association sub-problem and a power allocation sub-problem. For the former, optimum user association is determined by solving a Lagrangian dual problem with a sub-gradient algorithm; for the latter, optimum transmit powers of the BS and each relay station are determined by using Newton’s method. Finally, a sub-optimal solution of the original problem is obtained by a low-complexity iterative algorithm. Simulation results show that the proposed joint user association and power allocation algorithm can offload the traffic of the BS effectively, keep the BS and relay stations operate at low power levels, and improve the system energy efficiency significantly, compared with user association-only schemes.

Energy aware frame based fair scheduling

Energy has now-a-days become a critical resource in all battery operated devices. Reduction of energy consumption is essential to prolong the battery life in these systems. A significant class of such systems often execute a mix of independent real-time applications with guaranteed Quality of Service (QoS) requirements. Proportional fair schedulers form a very effective mechanism for handling such application sets, with high resource utilisation on multiprocessor systems. In this paper, we propose a DVFS enabled proportional fair strategy called Energy Aware Frame Based Fair Scheduling (EAFBFS) for executing a set of real-time QoS aware tasks on multicores. In addition to providing appreciable energy savings, EAFBFS is able to deliver high and tunable fairness accuracy, low scheduling related overheads along with resource utilisation optimality, by combining and leveraging the benefits of two prominent state-of-the-art schedulers ERFair and DPFair. While the proposed scheduler ensures atmost m−1 task migrations over stipulated intervals called time frames similar to DPFair, EAFBFS exhibits far improved fairness properties. Experimental results show that EAFBFS performs almost at par with energy aware DPFair in terms of energy savings and migrations incurred while achieving much higher proportional fairness accuracy (10–15 times on average over DPFair).

Optimal and Fair Energy Efficient Resource Allocation for Energy Harvesting-Enabled-PD-NOMA-Based HetNets

In this paper, the tradeoff among the energy efficiency, fairness, harvested energy, and system sum rate is studied. In this regard, various fairness methods, namely, max–min fairness, proportional fairness, and minimum delay potential fairness in power-domain non-orthogonal multiple access-based heterogeneous cellular networks are investigated. In order to perform successive interference cancellation (SIC), we use two ordering approaches and compare their performance. To this end, we propose joint subcarrier and power allocation algorithms to achieve fair energy efficient resource allocation for each fairness method and SIC ordering. Since the proposed optimization problems are non-convex and intractable, the existing methods to solve the convex problems could not be directly used. To overcome this difficulty, an iterative algorithm based on successive convex approximation is used. Moreover, to show the optimality gap of the proposed solution method, an optimal approach based on the monotonic optimization is applied in which we first transform each of the proposed optimization problems into a monotonic optimization problem of canonical form, and then, we obtain the optimal solution of each problem, which coincides with the optimal solution of the original non-convex problem. We finally study the performance of the proposed schemes using simulations for different values of the system parameters.

Robust Resource Allocation With Joint Carrier Aggregation in Multi-Carrier Cellular Networks

In this paper, we present a robust optimal resource allocation (RA) with joint carrier aggregation (CA) approach to allocate multiple carriers resources optimally among users with elastic and inelastic traffic in cellular networks. We use utility proportional fairness allocation policy, where the fairness among users is in utility percentage of the application running on the user equipment (UE). We introduce an efficient RA approach to allocate the network spectrum resources from multiple carriers based on a CA scenario. We present a robust RA algorithm that allocates optimal aggregated rates for both high-traffic and low-traffic situations. Our distributed RA algorithm allocates an optimal rate to each user from all carriers in its range while providing the minimum price for the allocated rate. In addition, we analyze the convergence of the algorithm with different network traffic densities and show that our algorithm provides traffic dependent pricing for network providers. Finally, we present simulation results for the performance of our RA algorithm.

Semistatic Cell Differentiation and Integration With Dynamic BBU-RRH Mapping in Cloud Radio Access Network

In this paper, a self-organizing cloud radio access network (C-RAN) is proposed, which dynamically adapt to varying network capacity demands. A load prediction model is considered for provisioning and allocation of base band units (BBUs) and remote radio heads (RRHs). The density of active BBUs and RRHs is scaled based on the concept of cell differentiation and integration (CDI) aiming efficient resource utilisation without sacrificing the overall quality of service (QoS). A CDI algorithm is proposed in which a semi-static CDI and dynamic BBU-RRH mapping for load balancing are performed jointly. Network load balance is formulated as a linear integer-based optimization problem with constraints. The semistatic part of CDI algorithm selects proper BBUs and RRHs for activation/deactivation after a fixed CDI cycle, and the dynamic part performs proper BBU to RRH mapping for network load balancing aiming maximum QoS with minimum possible handovers. A discrete particle swarm optimization (DPSO) is developed as an evolutionary algorithm to solve network load balancing optimization problem. The performance of DPSO is tested based on two problem scenarios and compared to genetic algorithm (GA) and the exhaustive search (ES) algorithm. The DPSO is observed to deliver optimum performance for small-scale networks and near optimum performance for large-scale networks. The DPSO has less complexity and is much faster than GA and ES algorithms. Computational results of a CDI-enabled C-RAN demonstrate significant throughput improvement compared to a fixed C-RAN, i.e., an average throughput increase of 45.53% and 42.102%, and an average blocked users reduction of 23.149%, and 20.903% is experienced for proportional fair and round Robin schedulers, respectively.

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

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 user's 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.

A low-complexity resource allocation scheme for OFDMA multicast systems with proportional fairness

A low-complexity optimization scheme is proposed to balance the tradeoff between system capacity and proportional fairness in orthogonal frequency division multiple access (OFDMA) based multicast systems. The major challenge is to solve the non-convexity optimization problem with strict proportional fairness. Constrained team progress algorithm (CTPA) solves this non-convexity problem by allocating sub-channels to each group based on sub-channel gains and proportional fairness constraint. Mapping power algorithm (MPA) guarantees strict proportional fairness with efficient power allocation which utilizes the mapping relation between power and throughput. CTPA-MPA is analyzed in three aspects: complexity, fairness and efficiency. We numerically show that when the system capacity is slightly increased in lower power region compared with several previous approaches, CTPA-MPA improves the proportional fairness in a typical scenario with 4 groups over 16 sub-channels, while reducing the complexity from exponential to linear in the number of sub-channels. It is also proved available in a more complicated system.

Developing a Video Buffer Framework for Video Streaming in Cellular Networks

This work proposes a new video buffer framework (VBF) to acquire a favorable quality of experience (QoE) for video streaming in cellular networks. The proposed framework consists of three main parts: client selection algorithm, categorization method, and distribution mechanism. The client selection algorithm was named independent client selection algorithm (ICSA), which is proposed to select the best clients who have less interfering effects on video quality and recognize the clients’ urgency based on buffer occupancy level. In the categorization method, each frame in the video buffer is given a specific number for better estimation of the playout outage probability, so it can efficiently handle so many frames from different videos at different bitrates. Meanwhile, at the proposed distribution mechanism, a predetermined threshold value is selected for lower and upper levels of playout outage probability. Then, the control unit at the base station will distribute the radio resources and decide the minimum rate requirement based on clients’ urgency categories. Simulation results showed that the VBF grantees fairness of resources distribution among different clients within the same cellular network while minimizing the interruption duration and controlling the video buffer at an acceptable level. Also, the results showed that the system throughput of the proposed framework outperforms other existing algorithms such as playout buffer and discontinuous reception aware scheduling (PBDAS), maximum carrier‐to‐interface ratio (MAX‐CIR), and proportional fair (PF) due to enhancing the quality of experience for video streaming by increasing the radio resources in fairness manner.

Optimal Frequency Reuse in HetNets With In-Band Relays

In-band relay nodes can be utilized to enhance the coverage of heterogeneous networks in a cost-effective way. However, the wireless backhaul links of in-band relay nodes also consume the limited spectrum resources. Appropriate spectrum resource management/cooperation is necessary to ensure the balanced resource usages between the macro base stations and the relay nodes. In this paper, we derive an optimal spectrum reuse strategy in a heterogeneous network with in-band relay nodes to maximize the overall proportional fairness metric. We first provide one distributed resource allocation algorithm based on the alternating direction method of multipliers for the heterogeneous network with in-band relay nodes. Even though the number of feasible spectrum reuse patterns increases exponentially with the total number of base stations and relay nodes, we further prove that we can achieve the optimal network performance by only activating a limited number of spectrum reuse patterns, which is just in the order of the total number of mobile stations and relay nodes. According to this finding, we put forth an algorithm to refine the set of active reuse patterns in a soft manner by employing the re-weighted $\ell _{1}$ -norm algorithm. Numerical simulations demonstrate the superiority and effectiveness of our proposed algorithms.

Multi-Element VLC Networks: LED Assignment, Power Control, and Optimum Combining

Visible light communications (VLCs) are a promising technology to address the spectrum crunch problem in radio frequency networks. A major advantage of VLC networks is that they can use the existing lighting infrastructure in indoor environments, which may have large number of LEDs for illumination. While LEDs used for lighting typically have limited bandwidth, presence of many LEDs can be exploited for indoor VLC networks, to serve each user by multiple LEDs for improving link quality and throughput. In this paper, LEDs are grouped and assigned to the users based on received signal strength from each LED, for which different solutions are proposed to achieve maximum throughput, proportional fairness, and quality of service. Additionally, power optimization of LEDs for a given assignment is investigated, and the Jacobian and Hessian matrices of the corresponding optimization problem are derived. Moreover, for multi-element receivers with LED grouping at the transmitter, an improved optimal combining method is proposed. This method suppresses interference caused by simultaneous data transfer of LEDs and improves the overall signal-to-interference-plus-noise-ratio by 2–5 dB. Lastly, an efficient calculation of channel response is presented to simulate multipath VLC channel with low computational complexity.

Weighted Proportional Fair Scheduling for Downlink Nonorthogonal Multiple Access

A weighted proportional fair (PF) scheduling method is proposed in the context of nonorthogonal multiple access (NOMA) with successive interference cancellation (SIC) at the receiver side. The new scheme introduces weights that adapt the classical PF metric to the NOMA scenario, improving performance indicators and enabling new services. The distinguishing value of the proposal resides in its ability to improve long‐term fairness and total system throughput while achieving a high level of fairness in every scheduling slot. Finally, it is shown that the additional complexity caused by the weight calculation has only a limited impact on the overall scheduler complexity, while simulation results confirm the claimed improvements, making the proposal an appealing alternative for resource allocation in a cellular downlink system.

基于比例公平调度算法的认知无线电系统性能分析

基于比例公平调度算法的认知无线电系统性能分析

Energy-Efficient Power Allocation with Rate Proportional Fairness Constraint in Non-Orthogonal Multiple Access Systems

Energy-Efficient Power Allocation with Rate Proportional Fairness Constraint in Non-Orthogonal Multiple Access Systems

Load-Balancing Scheme With Small-Cell Cooperation for Clustered Heterogeneous Cellular Networks

In this paper, a joint user association (UA) scheme with JP-CoMP using a hybrid self-organizing network (SON) is proposed for a practical clustered heterogeneous cellular network (cHCN) to maximize the network-wide proportional fairness among users. The cell range expansion and the enhanced intercell interference coordination have been considered as key items in the long-term evolution-advanced to offload macrocell users to small-cell base stations (sBSs). However, in a cHCN where sBSs are not distributed at random but are clustered instead, the coverage of inner sBSs in a small-cell cluster would be hardly expanded and an increased bias may result in much poor link quality as well as much higher load in outer sBSs. Thus, the load-balancing capability becomes much lower than expected in a cHCN. In order to cope with such a problem, a network architecture and protocol for the cHCN is suggested, and a feasible suboptimal iterative algorithm for determining the joint UA solution of the proposed hybrid SON is provided. It is shown that the proposed hybrid SON scheme with the proposed joint UA solution is very effective in handling the load balancing in a practical cHCN not only improving the performance of the inner sBS users by reducing the intercell interference, especially for intratier offloaded users, but also enabling more aggressive intertier offloading by effectively improving the link quality of cluster edge users without causing an unnecessary resource waste.

A Service‐Oriented Approach for Radio Resource Management in Virtual RANs

Virtualisation, as a key role player of future mobile communications, promotes the idea of service‐oriented architectures. This paper proposes a model of Radio Resource Management (RRM) for emerging Virtual Radio Access Networks, based on the interaction between two separated management entities: Common‐RRM (CRRM) to coordinate the radio resources among the Radio Access Technologies (RATs) and a centralised virtualisation platform on top of it, called Virtual‐RRM (VRRM), which is responsible for service orchestration among Virtual Network Operators, enabling the definition of various services and policies, separately from vendors and underlying RATs. The main objective of VRRM is to satisfy the Service Level Agreements associated with different service classes to the highest possible level, within the framework of proportional fairness. On the other hand, CRRM is in charge of mapping the demanded capacity of each service onto the most suitable RATs. The model is further extended to deal with extreme situations of resource shortage, resulting from high traffic loads, by introducing delay to lower priority services. The performance of the proposed model is evaluated in a practical multi‐RAT scenario. Results confirm that the isolation of service classes is consistent with the introduced serving weights, while all the demanded capacities from different services are responded by the most suitable RATs. Finally, independent of the variation of traffic load, 100% of the aggregated capacity is used.