Proportional fair scheduling with superposition coding in a cellular cooperative relay system

Many works have tackled on the problem of throughput and fairness optimization in cellular cooperative relaying systems. Considering firstly a two-user relay broadcast channel, we design a scheme based on superposition coding (SC) which maximizes the achievable sum-rate under a proportional fairness constraint. Unlike most relaying schemes where users are allocated orthogonally, our scheme serves the two users simultaneously on the same time-frequency resource unit by superposing their messages into three SC layers. The optimal power allocation parameters of each SC layer are derived by analysis. Next, we consider the general multi-user case in a cellular relay system, for which we design resource allocation algorithms based on proportional fair scheduling exploiting the proposed SC-based scheme. Numerical results show that the proposed algorithms allowing simultaneous user allocation outperform conventional schedulers based on orthogonal user allocation, both in terms of throughput and proportional fairness. These results indicate promising new directions for the design of future radio resource allocation and scheduling algorithms.     

Fairness based resource allocation for multiuser MISO-OFDMA systems with beamforming

Resource allocation problem in multiuser multiple input single output-orthogonal frequency division multiple access (MISO-OFDMA) systems with downlink beamforming for frequency selective fading channels is studied. The article aims at maximizing system throughput with the constraints of total power and bit error rate (BER) while supporting fairness among users. The downlink proportional fairness (PF) scheduling problem is reformulated as a maximization of the sum of logarithmic user data rate. From necessary conditions on optimality obtained analytically by Karush-Kuhn-Tucker (KKT) condition, an efficient user selection and resource allocation algorithm is proposed. The computer simulations reveal that the proposed algorithm achieves tradeoff between system throughput and fairness among users.     

Multi-user Fair Scheduling in the Downlink of CDMA Packet Systems

A fair scheduling algorithm is proposed to improve the system throughput while maintaining the fairness in the downlink of a code-division multiple access (CDMA) system employing AMC and multicodes. R. Kwan and C. Leung suggested an optimal scheduling to maximize the total throughput based on simultaneous transmissions strategy. In this letter, we extend the optimal scheduling so that some degree of fairness can be maintained. We formulate a mixed-integer nonlinear programming problem to assign the radio resources such as the transmit power and codes to several users effectively. The result shows that the proposed algorithm provides a significant throughput gain over PF scheduling with one-by-one transmission at the same level of fairness     

Inter‐cell coordinated beamforming with opportunistic scheduling

This paper proposes a distributed coordination framework with opportunistic scheduling among multiple users as opposed to the existing works on the multiple‐cell cooperative beamforming problem that deals with a single active user in each cell. In this cross‐layer design framework that deals with the beamforming in the physical layer and multiuser scheduling in the upper layer, radio resource management and inter‐cell coordination issues are jointly considered to improve the cell‐edge throughput performance by trading off their individual benefit in an optimal manner. Our simulation results demonstrated that its performance can reach up to 85% of its upper bound at the cell boundary. Copyright © 2015 John Wiley & Sons, Ltd.     

Prediction‐based MAC‐layer sensing in cognitive radio networks

We consider a cognitive radio network which coexists with multiple primary users (PUs) and secondary users (SUs) transmit over time‐varying channels. In this scenario, one problem of the existing work is the poor performances of throughput and fairness due to variances of SUs' channel conditions and PUs' traffic patterns. To solve this problem, we propose a novel prediction‐based MAC‐layer sensing algorithm. In the proposed algorithm, the SUs' channel quality information and the probability of the licensed channel being idle are predicted. Through the earlier predicted information, we schedule the SUs to sense and transmit on different licensed channels. Specifically, multiple significant factors, including network throughput and fairness, are jointly considered in the proposed algorithm. Then, we formulate the prediction‐based sensing scheduling problem as an optimization problem and solve it with the Hungarian algorithm in polynomial time. Simulation results show that the proposed prediction‐based sensing scheduling algorithm could achieve a good tradeoff between network throughput and fairness among SUs. Copyright © 2014 John Wiley & Sons, Ltd.     

A flexible downlink scheduling scheme in cellular packet data systems

Fast downlink scheduling algorithms play a central role in determining the overall performance of high-speed cellular data systems, characterized by high throughput and fair resource allocation among multiple users. We propose a flexible channel-dependent downlink scheduling scheme, named the (weighted) alpha-rule, based on the system utility maximization that arises from the Internet economy of long-term bandwidth sharing among elastic-service users. We show that the utility as a function of per-user mean throughput naturally derives the alpha-rule scheme and a whole set of channel-dependent instantaneous scheduling schemes following different fairness criteria. We evaluate the alpha-rule in a multiuser CDMA high data rate (HDR) system with space-time block coding (STBC) or Bell Labs layered space-time (BLAST) multiple-input multiple-output (MIMO) channel. Our evaluation shows that it works efficiently by enabling flexible tradeoff between aggregate throughput, per-user throughput, and per-user resource allocation through a single control parameter. In other words the Alpha-rule effectively fills the performance gap between existing scheduling schemes, such as max-C/I and proportional fairness (PF), and provides an important control knob at the media-access-control (MAC) layer to balance between multiuser diversity gain and location-specific per-user performance.     

Proportional Fairness in Multi-Channel Multi-Rate Wireless Networks?Part II: The Case of Time-Varying Channels with Application to OFDM Systems

This is Part II of a two-part paper series that studies the use of the proportional fairness (PF) utility function as the basis for resource allocation and scheduling in multichannel multi-rate wireless networks. The contributions of Part II are twofold. (i) First, we extend the problem formulation, theoretical results, and algorithms to the case of time-varying channels, where opportunistic resource allocation and scheduling can be exploited to improve system performance. We lay down the theoretical foundation for optimization that ?couples? the time-varying characteristic of channels with the requirements of the underlying applications into one consideration. In particular, the extent to which opportunistic optimization is possible is not just a function of how fast the channel characteristics vary, but also a function of the elasticity of the underlying applications for delayed resource allocation. (ii) Second, building upon our theoretical framework and results, we study subcarrier allocation and scheduling in orthogonal frequency division multiplexing (OFDM) cellular wireless networks. We introduce the concept of a W-normalized Doppler frequency to capture the extent to which opportunistic scheduling can be exploited to achieve throughput-fairness performance gain. We show that a ?lookback PF? scheduling can strike a good balance between system throughput and fairness while taking the underlying application requirements into account.     

Scheduling schemes for multimedia service in wireless OFDM systems

Scheduling schemes play a key role in the system performance of broadband wireless systems such as WLANs/WMANs. Maximal SNR and round robin are two conventional scheduling strategies that emphasize efficiency and fairness, respectively. The proportional fair scheme provides a trade-off between efficiency and fairness, and has been well studied in TDMA and CDMA systems. In this article we extended the PF scheduling scheme to OFDM-based BWSs (OPF). In addition, we propose three variations: adaptive OPF (AOPF), multimedia AOPF (MAOPF), and normalized MAOPF (NMAOPF) in order to meet the QoS requirements for multirate services in multimedia systems. The adaptive modulation and coding schemes in time varying and frequency selective fading are considered. The system performances of the algorithms are compared in terms of efficiency (throughput and mean packet delay) and fairness (user satisfaction rate and average user rate). Joint physical and media access control layer simulation results show that AOPF and MAOPF can improve throughput at the cost of fairness, and NMAOPF can provide the highest throughput without losing fairness.     

Differentiated rate scheduling for the down-link of cellular systems

We consider the problem of differentiated rate scheduling for the downlink (i.e., multi-antenna broadcast channel), in the sense that the rates required by different users must satisfy certain constraints on their ratios. When full channel state information (CSI) is available at the transmitter and receivers, the problem can be readily solved using dirty paper coding (DPC) and the application of convex optimization techniques on the dual problem which is the multiple access channel (MAC). Since in many practical application full CSI may not be feasible and computational complexity prohibitive when the number of users is large, we focus on other simple schemes that require very little CSI: time-division opportunistic (TO) beamforming where in different time slots (of different lengths) the transmitter performs opportunistic beamforming to the users requiring the same rate, and weighted opportunistic (WO) beamforming where the random beams are assigned to those users having the largest weighted SINR. For single antenna systems we also look at the capacity-achieving superposition coding (SC) scheme. In all cases, we determine explicit schedules to guarantee the rate constraints and show that, in the limit of large number of users, the throughput loss compared to the unconstrained throughput (sum-rate capacity) tends to zero. We further provide bounds on the rate of convergence of the sum-rates of these schemes to the sum-rate capacity. Finally, we provide simulation results of the performance of different scheduling schemes considered in the paper.     

Opportunistic Beamforming and Scheduling for OFDMA Systems

Orthogonal frequency-division multiple access (OFDMA) is an attractive technique for exploiting multiuser diversity in the downlink of a cellular system. This paper addresses three problems in multiuser diversity for OFDMA systems. First, we propose a way to significantly reduce the amount of channel state information (CSI) feedback without sacrificing performance too much, by selective and adaptive feedback. Second, we propose a way to increase the cell throughput and fairness by applying an opportunistic beamforming scheme to orthogonal frequency-division multiplexing. This beamforming scheme increases the frequency fading rate, which increases the multiuser diversity effect. Thirdly, we deal with the issue of fairness and quality-of-service (QoS) in opportunistic systems by proposing a modified proportional fair (PF) scheduler for OFDMA. Key features in the scheduler are that it incorporates QoS classes into the PF scheduler and that it has a tunable fairness level. Extensive simulation results are presented to evaluate the performance of the proposed schemes. The opportunistic beamforming scheme performed well in comparison with several other schemes. The modified PF scheduler was able to give users different QoS, based on their requirements, while still exploiting multiuser diversity     

Distributed Proportional Fair Scheduling for IEEE802.11 Wireless LANs

In the time varying wireless channel, opportunistic scheduling is one of the important techniques to achieving the rich diversities inherent in wireless communications. However, most existing scheduling schemes require centralized scheduling and little work has been done on developing distributed algorithms The proportional fair scheduling is one of the representative opportunistic scheduling for centralized networks. In this paper, we propose distributed proportional fair scheduling (DPFS) scheme for wireless LAN network. In the proposed DPFS scheme, each receiver estimates channel condition and calculates independently its own priority with probabilistic manner, which can reduce excessive probing overhead required to gather the channel conditions of all receivers. We evaluate the proposed DPFS using extensive simulation and simulation results show that DPFS obtains higher network throughput than conventional scheduling schemes while maintaining fairness among users.     

Optimal and Approximate Mobility-Assisted Opportunistic Scheduling in Cellular Networks

This paper considers the problem of scheduling multiple users in the downlink of a time-slotted cellular data network. For such a network, opportunistic scheduling algorithms improve system performance by exploiting time variations of the radio channel. We present novel optimal and approximate opportunistic scheduling algorithms that combine channel fluctuation and user mobility information in their decision rules. The algorithms modify the opportunistic scheduling framework of Liu et al., (1993) with dynamic constraints for fairness. These fairness constraints adapt according to the user mobility. The adaptation of constraints in the proposed algorithms implicitly results in giving priority to the users that are in the most favorable locations. The optimal algorithm is an offline algorithm that precomputes constraint values according to a known mobility model. The approximate algorithm is an online algorithm that relies on the future prediction of the user mobility locations in time. We show that the use of mobility information in opportunistic scheduling increases channel capacity. We also provide analytical bounds on the performance of the approximate algorithm using the fundamental inequality of Dyer et al., (1986) for linear programs. Simulation results on high data rate (HDR) illustrate the usefulness of the proposed schemes for elastic traffic and macrocell structures     

Opportunistic Scheduling with QoS Constraints for Multiclass Services HSUPA System

This paper focuses on the scheduling problem with the objective of maximizing system throughput, while guaranteeing long‐term quality of service (QoS) constraints for non‐realtime data users and short‐term QoS constraints for realtime multimedia users in multiclass service high‐speed uplink packet access (HSUPA) systems. After studying the feasible rate region for multiclass service HSUPA systems, we formulate this scheduling problem and propose a multi‐constraints HSUPA opportunistic scheduling (MHOS) algorithm to solve this problem. The MHOS algorithm selects the optimal subset of users for transmission at each time slot to maximize system throughput, while guaranteeing the different constraints. The selection is made according to channel condition, feasible rate region, and user weights, which are adjusted by stochastic approximation algorithms to guarantee the different QoS constraints at different time scales. Simulation results show that the proposed MHOS algorithm guarantees QoS constraints, and achieves high system throughput.     

Physical layer techniques and maximum throughput scheduling with antenna arrays

We consider the downlink of a wireless system, where a base station transmits to users with an antenna array. We introduce scheduling algorithms that employ randomization to achieve maximum throughput, at low computational complexity. The algorithms operate in conjunction with either one of two physical layer techniques, namely transmit beamforming and Costa precoding. Simulation results show that the proposed randomized scheduling with Costa precoding algorithms carry the superior performance of Costa precoding at the physical, over to throughput benefits at higher layers.     

Fair TDMA scheduling in wireless multihop networks

In wireless multihop networks, communication between two end-nodes is carried out by hopping over multiple wireless links. However, the fact that each node has to transmit not only its own traffic, but also traffic on behalf of other nodes, leads to unfairness among the communication rates of the nodes. Traditional Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) based media access control does not work satisfactory in a multihop scenario, since an intended target of a communication may be subject to mutual interference imposed by concurrent transmissions from nodes, which cannot directly sense each other, thus causing unfair throughput allocation. Although Time Division Multiple Access (TDMA) seems to be a more promising solution, careful transmission scheduling is needed in order to achieve error-free communication and fairness. Several algorithms may be found in the literature for scheduling TDMA transmissions in wireless multihop networks. Their main goal is to determine the optimal scheduling, in order to increase the capacity and reduce the delay for a given network topology, though they do not consider the traffic requirements of the active flows of the multihop network or fairness issues. In this paper, we propose a joint TDMA scheduling/load balancing algorithm, called Load-Balanced-Fair Flow Vector Scheduling Algorithm (LB-FFVSA). This algorithm schedules the transmissions in a fair manner, in terms of throughput per connection, taking into account the communication requirements of the active flows of the network. Simulation results show that the proposed algorithm achieves improved performance compared to other solutions, not only in terms of fairness, but also in terms of throughput. Moreover, it was proved that when a load balancing technique is used, the performance of the scheduling algorithm is further improved.     

Proportional Fairness in Multi?Carrier System with Multi?Slot Frames: Upper Bound and User Multiplexing Algorithms

Optimal Proportional Fair Scheduling (PFS) in a multi-carrier system is a prohibitively complex combinatorial problem. In this paper we consider practical time frames with multiple time slots, where this optimal allocation becomes even more complex. Therefore, we derive bounds for the optimal proportional fair allocation, by means of convex optimization, and propose approximation algorithms where several users can be time-multiplexed on a same subchannel. With a much lower complexity than the optimal allocation, these algorithms achieve an excellent tradeoff between throughput and proportional fairness, even with the increased signaling overhead.     

Opportunistic Scheduling: Generalizations to Include Multiple Constraints,Multiple Interfaces,and Short Term Fairness

We consider several scheduling problems for packet based systems with time-varying channel conditions. Designing scheduling mechanisms that take advantage of time-varying channel conditions, which are different for different users, is necessary to improve system performance; however this has to be done in a way that provides some level of fairness among the users. Such scheduling mechanisms are termed opportunistic. We generalize the opportunistic scheduling mechanisms in the literature on three fronts. First, we formulate and solve an opportunistic scheduling problem with multiple general long term QoS constraints and a general system objective function. The solution of this opportunistic scheduling problem is an index policy. Then, we generalize this problem to include multiple interface systems in which several users can be served simultaneously. Apart from the long term QoS constraints specified by each user, multiple interface systems are constrained with other physical limitations imposed by the system. We show that the structure of the optimal opportunistic scheduling policy is carried over to the problem with general constraints and multiple interfaces. We also study the stability of the multiple interface systems and propose a throughput optimal scheduling rule for such systems. We then formulate an opportunistic scheduling problem with short term processor sharing fairness constraints as an optimization problem where fairness is guaranteed over a finite time window. In its most general form, this problem cannot be solved analytically. Hence observing the form of the optimal policies for special cases, we propose a heuristic scheduling policy. We illustrate the effectiveness of the policies via simulation.Sunil Suresh Kulkarni obtained his M.E. (1999) degree in Electrical Communication from Indian Institute of Science (IISc) Bangalore, and B.E. (1997) in Electronics Engineering from Walchand College of Engineering, Sangli. He is currently pursuing his Ph.D. in School of Electrical and Computer Engineering at Purdue University and also pursuing M.S in Department of Mathematics. Before joining for Ph.D program he worked as software engineer in India. His research interests include wireless cellular networks, ad-hoc and sensor networks and performance modelling of communication networks.Catherine Rosenberg Born and educated in France (Ecole Nationale Supérieure des Téléxcommunications de Bretagne, Diplome d’Ingénieur in EE in 1983 and University of Paris, Orsay, Doctorat en Sciences in CS in 1986) and in the USA (UCLA, MS in CS in 1984), Dr. Rosenberg has worked in several countries including USA, UK, Canada, France and India. In particular, she worked for Nortel Networks in the UK, AT&T Bell Laboratories in the USA, Alcatel in France and taught at Ecole Polytechnique of Montreal (Canada).Dr. Rosenberg is currently Professor in the School of Electrical and Computer Engineering at Purdue University. She is also the Director of the university-wide Center for Wireless Systems and Applications at Purdue University.Agencies and industries that have supported her research include NSERC (The Canadian NSF), FCAR (The Quebec counterpart of NSERC), CRC (Canadian Ministry of Communications), EEC (European Commission), ESA (European Space Agency), France-Telecom, CISCO, and Nortel Networks.Her research interests are in broadband networks (IP and ATM), in wireless networking, in network security, peer-to-peer networks, and in traffic engineering (QoS, Charging, Dynamic Provisioning, Network Design, and Routing). She has authored over 70 papers on ATM, satellite broadband networking, wireless networking, and traffic engineering and has filed several patents in the UK and the USA.     

A unified framework for opportunistic fair scheduling in wireless networks: a dual approach

In this paper, we propose a unified framework for opportunistic fair scheduling in wireless systems. We consider a TDMA type of multiple access scheme, in which only one user can be scheduled in each time-slot. For opportunistic fair scheduling in such a system, some nice frameworks have been developed in the previous works, such as Agrawal and Subramanian (Allerton conference on communication, control and computing, 2002), Liu et al. (IEEE Journal of Selected Areas in Communications 19(10): 2053–2065, 2001) and Liu et al. (Computer Networks 41(4): 451–474, 2003). However, in this paper, we consider a more general problem that can accommodate more general types of fairness, and more general types of utility functions than those in the previous works. In addition to those generalizations, we develop a new framework for opportunistic fair scheduling based on the duality theory, which is different from those in the previous works. The duality theory is a well-defined theory in the mathematical optimization area. Hence, it can provide a unified framework for many different types of problems. In fact, we show that two different frameworks in Agrawal and Subramanian (Allerton conference on communication, control and computing, 2002), Liu et al. (IEEE Journal of Selected Areas in Communications 19(10): 2053–2065, 2001) and Liu et al. (Computer Networks 41(4): 451–474, 2003) are special cases of ours. In addition, by using the unified framework developed in this paper, we can not only develop various opportunistic fair scheduling schemes but also analyze the developed algorithm more rigorously and systematically.     

On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming

Although the capacity of multiple-input/multiple-output (MIMO) broadcast channels (BCs) can be achieved by dirty paper coding (DPC), it is difficult to implement in practical systems. This paper investigates if, for a large number of users, simpler schemes can achieve the same performance. Specifically, we show that a zero-forcing beamforming (ZFBF) strategy, while generally suboptimal, can achieve the same asymptotic sum capacity as that of DPC, as the number of users goes to infinity. In proving this asymptotic result, we provide an algorithm for determining which users should be active under ZFBF. These users are semiorthogonal to one another and can be grouped for simultaneous transmission to enhance the throughput of scheduling algorithms. Based on the user grouping, we propose and compare two fair scheduling schemes in round-robin ZFBF and proportional-fair ZFBF. We provide numerical results to confirm the optimality of ZFBF and to compare the performance of ZFBF and proposed fair scheduling schemes with that of various MIMO BC strategies.     

Differentiated TCP User Perception over Downlink Packet Data Cellular Systems

Current downlink scheduling algorithms in the (enhanced) third-generation (3G) cellular packet systems exploit instantaneous channel status of multiple users, but most of them are blind to traffic information. To improve TCP users' perception of quality-of-services (QoSs), characterized by response delay, goodput, and always-on connectivity, we propose a cross-layer hierarchical scheduler with traffic awareness and channel dependence to properly prioritize buffer and radio resource allocation among different TCP classes. The scheduler has two tiers: at the IP layer, an intrauser scheduler enhances a common practice, i.e., the DiffServ-based buffer management, by dequeuing same-user TCP packets according to per-class specified and measured responsiveness; at the MAC layer, an interuser scheduler transmits the dequeued packets by considering the opportunistic channel states, mean throughput, and class ID of all users. Both tiers consider the online measured throughput, a cross-layer metric, to achieve resource and performance fairness and TCP classification. Experiments show that, compared with (variations of) proportional fairness (PF) and other schemes, our scheduler can notably speed up time-critical interactive TCP services (HTTP and TELNET) or TCP slow-starts with minor cost to bulk file transfer (FTP) or long-lived flows. It offers scalable and low-cost TCP performance enhancement over the emerging cellular systems