A modified proportional fairness (PF) scheduling scheme for OFDMA systems with imperfect channel quality indicator is suggested. It is based on user grouping, and in system level simulations, the proposed scheme improves average user throughput considerably when compared to conventional PF scheduling without grouping.

This letter introduces a new fairness concept, namely proportional quasi-fairness and proves that the optimal end-to-end rate of a network utility maximization can be proportionally quasi-fair with a properly chosen network utility function for an arbitrary compact feasible set.

In this paper, we mathematically derive a matrix-form solution named resource allocation matrix (RAM) for sub-band allocation in an orthogonal frequency division multiple access (OFDMA) system. The proposed scheme is designed to enhance throughput under a strict user fairness condition such that every user has an equal number of sub-bands per frame. The RAM designates the most preferable sub-band for every user. The proposed scheme is evaluated in terms of throughput and user fairness by comparison with the proportional fairness (PF) scheme and greedy scheme. Numerical results show that the proposed scheme has overwhelming superiority to other schemes in terms of fairness and tight competitive in terms of throughput.

The biggest challenge in multi-cell MIMO multiplexing systems is how to effectively suppress the other-cell interference (OCI) since the OCI severely decrease the system performance. Cooperation among cells is one of the most promising solutions to OCI problems. However, this solution suffers greatly from delay and overhead issues, which make it impractical. A coordinated MIMO system with a simplified cooperation between the base stations is a compromise between the theory and practice. We aim to devise an effective resource allocation algorithm based on a coordinated MIMO system that largely alleviates the OCI. In this paper, we propose a joint resource allocation algorithm incorporating intra-cell beamforming multiplexing and inter-cell interference suppression, which adaptively allocates the transmitting power and schedules users while achieving close to an optimal system throughput under proportional fairness consideration. We formulate this problem as a nonlinear combinational optimization problem, which is hard to solve. Then, we decouple the variables and transform it into a problem with convex sub-problems that can be solve but still need heavy computational complexity. In order to implement the algorithm in real-time scenarios, we reduce the computational complexity by assuming an equal power allocation utility to do user scheduling before the power allocation. Extensive simulation results show that the joint resource allocation algorithm can achieve a higher throughput and better fairness than the traditional method while maintains the proportional fairness. Moreover, the low-complexity algorithm obtains a better fairness and less computational complexity with only a slight loss in throughput.

Proportional fair scheduling attains a graceful trade-off between fairness among users and total system throughput. It is simple to implement in single carrier transmission systems, while changes to a prohibitively complex combinatorial problem for multi-carrier transmission systems. This letter addresses a couple of conditions that approximate multi-carrier proportional fair scheduling (MCPF) as carrier-by-carrier proportional fair scheduling (CCPF), which has much lower complexity than MCPF. Numerical results show that the proportional fairness metric of CCPF approaches to that of MCPF for those conditions.

This paper proposes a robust state observer for multi-input multi-output LTI systems. Unknown inputs of polynomial form and high-frequency measurement noises are considered in the system model. The unknown inputs and the noises are not in the same form. Multiple integrations of both the observer error signal and the measurement output are used for the observer design. The existence condition of the proposed observer is shown to be the same as that of the proportional-integral (PI) observer. Computer simulations show the effectiveness of the proposed observer.

This paper considers the proportional fair (PF) based subcarrier allocation problem in a multihop orthogonal frequency division multiple access (OFDMA) broadcast system with decode-and-forward (DF) relays. The problem is formulated as a mixed binary integer programming problem with the objective to achieve proportional fairness among users and exploit the diversity provided by the independent frequency selective fading among hops. Since it is prohibitive to find the optimal solution, two efficient heuristic schemes are proposed. Simulation results indicate that with the same fairness performance, the proposed schemes achieve considerable capacity gain over the conventional PF scheduling method.

In this paper, we propose a scheme of frequency sub-band allocation to obtain maximum throughput in an orthogonal frequency division multiple access (OFDMA) system where each user has a finite number of packets to transmit, which are generated from packet calls with arbitrary size and arbitrary arrival rate. The proposed scheme is evaluated in terms of throughput and user fairness in comparison with the proportional fairness (PF) scheme and the Greedy scheme under the finite queue length condition. Numerical results show that the proposed scheme is superior to the Greedy scheme in terms of both throughput and fairness for finite queue length.

We have developed a novel downlink packet scheduling scheme for a multiuser OFDMA system in which a subchannel can be time-multiplexed among multiple users. This scheme which is called Matrixed-based Proportional Fairness can provide a high system throughput while ensuring fairness. The scheme is based on a Proportional Fairness (PF) utility function and can be applied to any of the PF-based schedulers. Our scheduler explores multichannel multiuser diversity by using a two-dimensional matrix combining user selection, subchannel assignment, and time slot allocation. Furthermore, unlike other PF-based schemes, our scheme considers finitely backlogged queues during the time slot allocation. By doing so, it can exploit multichannel multiuser diversity to utilize bandwidth efficiently and with throughput fairness. Additionally, fairness in the time domain is enhanced by limiting the number of allocated time slots. Intensive simulations considering finitely backlogged queues and user mobility prove the scheme's effectiveness.

In this paper, we focus on the adaptive resource allocation issue for uplink OFDMA systems. The resources are allocated according to a proportional fairness criterion, which can strike an alterable balance between fairness and efficiency. Optimization theory is used to analyze the multi-constraint resource allocation problem and some heuristic characteristics about the optimal solution are obtained. To deal with the cohesiveness of the necessary conditions, we resort to bargaining theory that has been deeply investigated in game theory. Firstly, we summarize some assumptions about bargaining theory and show their similarities with the resource allocation process. Then we propose a priority-ranked bargaining model, whose primary contribution is applying the economic thought to the resource allocation process. A priority-ranked bargaining algorithm (PRBA) is subsequently proposed to permit the base station to auction the subcarriers one by one according to the users' current priority. By adjusting the predefined rate ratio flexibly, PRBA can achieve different degrees of fairness among the users' capacity. Simulation results show that PRBA can achieve similar performance of the max-min scheme and the NBS scheme in the case of appropriate predefined rate ratio.

A parallel multiplexing scheduling (PMS) scheme is proposed for distributed antenna systems (DAS), which greatly improves average system throughput due to multi-user diversity and multi-user multiplexing. However, PMS has poor fairness because of the use of the "best channel selection" criteria in the scheduler. Thus we present a parallel proportional fair scheduling (PPFS) scheme, which combines PMS with proportional fair scheduling (PFS) to achieve a tradeoff between average throughput and fairness. In PPFS, the "relative signal to noise ratio (SNR)" is employed as a metric to select the user instead of the "relative throughput" in the original PFS. And only partial channel state information (CSI) is fed back to the base station (BS) in PPFS. Moreover, there are multiple users selected to transmit simultaneously at each slot in PPFS, while only one user occupies all channel resources at each slot in PFS. Consequently, PPFS improves fairness performance of PMS greatly with a relatively small loss of average throughput compared to PFS.

Several scheduling algorithms have been proposed for the downlink of a Code Division Multiple Access (CDMA) system with High Data Rate (HDR). Modified Largest Weighted Delay First (M-LWDF) scheduling algorithm selects a user according to the user current channel condition, user head-of-line packet delay and user Quality of Service (QoS) requirement. Proportional Fair (PF) scheduling algorithm has also been proposed for CDMA/HDR system and it selects a user according to the ratio of the user current channel rate and the user average channel rate, which provides good performance in terms of fairness. However, when variable bit rate (VBR) traffic is considered under different channel conditions for each user, both schedulers' performance decrease. M-LWDF scheduler can not guarantee the QoS requirement to be achieved and PF scheduler can not achieve a good fairness among the users. In this work, we propose a new scheduling algorithm to enhance M-LWDF and PF schedulers performance. Proposed scheduler selects a user according to the user input traffic characteristic, user current channel condition and user QoS requirement, which consists of a delay value with a maximum violation probability. We consider the well-known effective bandwidth expression, which takes into account the user QoS requirement and the user input traffic characteristics, to select a user to be scheduled. Properties of the proposed scheduling algorithm are investigated through simulations with constant bit rate (CBR) and VBR flows and performance comparisons with M-LWDF and PF schedulers. The results show a better performance of the proposed scheduler compared with M-LWDF and PF schedulers.

We study the interaction of TCP and the proportional fair scheduling algorithm in wireless networks. We show that the additive increase and multiplicative decrease algorithm of TCP can favor bad channel users, which results in inefficient use of radio resources. To remedy the problem, a proportional queue management scheme is proposed. The effectiveness of the algorithm is shown by simulations.

Unstructured overlay networks are widely adopted in large-scale and heterogeneous peer-to-peer (P2P) systems for their scalability and flexibility. A distinct feature of such systems is that they randomly route messages e.g., by flooding or random walk. In such systems, the number of messages and tasks carrying by those messages each peer receives is greatly affected by the number of the peer's incoming links. The objective of this paper is to build controllable degree-weighted networks in which the expected number of incoming links of each peer is proportional to its weight which is a local parameter. In such a network, a peer can control the number of those randomly disseminated messages and tasks it receives by adjust it weight. In addition, in order to bound the construction overhead for highly biased networks, we restrict all peers to have the same number of outgoing links. The objective network is constructed by local topology transformations that peers periodically exchange outgoing links with each other. A framework, which includes 81 different protocols by combination of exchange rules, is presented and evaluated by simulation. The simulation result shows that two of them can generate the networks having similar properties with the objective network. This work first achieves the weight-proportional degree control under the out-regular network model.

Orthogonal Frequency Division Multiple Access (OFDMA) is the technique for the next generation wireless networks, whose enhanced capacity is to serve a combination of traffic with diverse QoS requirements. To realize this, the resource allocation scheme has to be carefully designed so that the instantaneous channel condition, QoS provision, and the network utilization are integrated. In this paper, we propose the resource allocation scheme for downlink traffic of 2 classes; guaranteed and non-guaranteed, having different traffic contracts. We provide guaranteed throughput for the guaranteed class by considering the cost incurred from serving this class. Then, we formulate the assignment problem with the objective of minimizing this cost. For the non-guaranteed class, we aim to maximize network utilization and to maintain throughput fairness, by employing Proportional Fairness (PF) utility function and emphasizing on the portion of network resource that the user received and the individual user's queue length. We use a heuristic approach to schedule users' data into the downlink subframe by exploiting multi-user multi-channel diversity to utilize system's bandwidth efficiently. Intensive simulation shows that our scheme differentiates classes of traffic and provides satisfied throughput, lower packet drop rate, and lower queuing delay to the guaranteed class, comparing with those of the non-guaranteed class. Furthermore, the results also show that the scheme is fair to users in the same class in both throughput and service time.

This paper considers a proportional fairness of end-to-end session rates in a multihop wireless network through the rate control framework. In multihop wireless networks, there are two classes of rate control problem. One focuses in optimizing the transmission attempt probabilities at the lower layers, but not the transmit powers while other problem is closely related to jointly optimal congestion control and power control. Proportional fairness is a fundamental concept in flow control problems. In this paper, we give in-depth analysis and show that the optimal solutions of these problems are proportionally fair provided that the objective functions are suitably chosen.

In this paper, we investigate the proportional fair scheduling (PFS) problem for multiuser OFDM systems, considering the impact of packet length. Packet length influences scheduling schemes in a way that each scheduled packet should be ensured to be completely transmitted within the scheduled frames. We formulate the PFS problem as an optimization problem. Based on the observations on the structure of optimal solutions, we propose a heuristic scheduling algorithm that consists of two stages. First, subcarriers are allocated among users without considering the packet length constraint. Then on the second stage, subcarrier readjustment is done in a way that surplus subcarriers from length-satisfied users are released and allocated among length-unsatisfied users. The objective is to provide proportional fairness among users while guaranteeing complete transmission of each scheduled packet. Simulation results show that the proposed scheme has quite close performance to the optimal scheme in terms of Multi-carrier Proportional Fairness Measure (MCPFM), throughput and average packet delay.

We present a TCP flow level performance evaluation on error rate aware scheduling algorithms in Evolved UTRA and UTRAN networks. With the introduction of the error rate, which is the probability of transmission failure under a given wireless condition and the instantaneous transmission rate, the transmission efficiency can be improved without sacrificing the balance between system performance and user fairness. The performance comparison with and without error rate awareness is carried out dependant on various TCP traffic models, user channel conditions, schedulers with different fairness constraints, and automatic repeat request (ARQ) types. The results indicate that error rate awareness can make the resource allocation more reasonable and effectively improve the system and individual performance, especially for poor channel condition users.

Service differentiation is one of the key issues in the current Internet. In this paper, we focus on a recent proposal for proportional loss rate differentiation which employs a single FIFO queue, an AQM algorithm for computing the packet drop probability, and a counter-based packet dropping routine for achieving the intended proportional loss rate differentiation among classes. It is first shown that, when the target dropping probability of a class is large, the counter-based packet dropping routine may yield a significant amount of error between the target and measured drop probabilities for the class, and subsequently, fails to maintain the loss rate ratios between classes as intended. To avoid this problem, a new compensatory packet dropping routine is developed in this paper. Then, a series of simulation experiments are conducted using the ns-2 simulator to assess the performances of the two dropping routines under various congestion conditions and quality spacings between classes. The simulation results show that, unlike the counter-based dropping routine, the proposed compensatory dropping routine is effective in keeping the loss rate ratios between classes closely on target regardless of the degree of congestion and quality spacing between classes, while the two dropping routines perform similarly in terms of throughput and queueing delay in the bottleneck link. In addition, such robustness of the proposed routine is achieved without any additional control parameter or computational effort compared to the counter-based routine.

We investigate the issues involved in designing a packet scheduler for the proportional delay differentiation (PDD) model in differentiated services (DiffServ) networks. The PDD model controls the average waiting time of each class such that the average waiting time is proportional to its corresponding delay differentiation parameter. This paper proposes a novel packet scheduler for PDD referred to as the longest waiting time first (LWTF). By adding certain conditions, we found that the LWTF scheduler can be reduced to a known packet scheduler-priority queue with linear priorities (PQ-LP). The properties and behaviors of LWTF can be predicted from the analysis of PQ-LP. The simulation results in comparison with other PDD algorithms have also revealed that LWTF provides no worse level of service quality in long timescales and affords more accurate and robust control over the delay ratio in short timescales.