Opportunistic Scheduling Research Articles

A General Framework for Temporal Fair User Scheduling in NOMA Systems

Non-orthogonal multiple access (NOMA) is one of the promising radio access techniques for next generation wireless networks. Opportunistic multi-user scheduling is necessary to fully exploit multiplexing gains in NOMA systems, but compared with traditional scheduling, interrelations between users' throughputs induced by multi-user interference poses new challenges in the design of NOMA schedulers. A successful NOMA scheduler has to carefully balance the following three objectives: maximizing average system utility, satisfying desired fairness constraints among the users and enabling real-time, and low computational cost implementations. In this paper, scheduling for NOMA systems under temporal fairness constraints is considered. Temporal fair scheduling leads to communication systems with predictable latency as opposed to utilitarian fair schedulers for which latency can be highly variable. It is shown that optimal system utility is achieved using a class of opportunistic scheduling schemes called threshold based strategies (TBS). One of the challenges in temporal fair scheduling for heterogeneous NOMA scenarios - where only specific users may be activated simultaneously - is to determine the set of feasible temporal shares. In this work, a variable elimination algorithm is proposed to accomplish this task. Furthermore, an (online) iterative algorithm based on the Robbins-Monro method is proposed to construct a TBS by finding the optimal thresholds for a given system utility metric. Various numerical simulations of practical scenarios are provided to illustrate the effectiveness of the proposed NOMA scheduling in static and mobile scenarios.

Utility Optimal Scheduling for Coded Caching in General Topologies

We consider coded caching over the fading broadcast channel, where the users, equipped with a memory of finite size, experience asymmetric fading statistics. It is known that a naive application of coded caching over the channel at hand performs poorly especially in the regime of a large number of users due to a vanishing multicast rate. We overcome this detrimental effect by a careful design of opportunistic scheduling policies such that some utility function of the long-term average rates should be maximized while balancing fairness among users. In particular, we propose a threshold-based scheduling that requires only statistical channel state information and one-bit feedback from each user. More specifically, each user indicates via feedback whenever its SNR is above a threshold determined solely by the fading statistics and the fairness requirement. Surprisingly, we prove that this simple scheme achieves the optimal utility in the regime of a large number of users. Numerical examples show that our proposed scheme performs closely to the scheduling with full channel state information, but at a significantly reduced complexity.

A Whittle's Index Based Approach for QoE Optimization in Wireless Networks

The design of schedulers to optimize heterogeneous users' Quality of Experience (QoE) remains a challenging and important problem for wireless systems. Our paper ([1]) explores three inter-related aspects of this problem: 1) non-linear relationships between a user's QoE and flow delays; 2) managing load dependent QoE trade-offs among heterogeneous application classes; and 3), striking a good balance between opportunistic scheduling and greedy QoE optimization. To that end we study downlink schedulers which minimize the expected cost modeled by convex functions of flow delays for users with heterogeneous channel rate variations. The essential features of this challenging problem are modeled as a Markov Decision Process to which we apply Whittle's relaxation, which in turn is shown to be indexable. Based on the Whittle's relaxation we develop a new scheduling policy, Opportunistic Delay Based Index Policy (ODIP). We then prove various structural properties for ODIP which result in closed form expressions for Whittle's indices under different scheduler scenarios. Using extensive simulations we show that ODIP scheduler provides a robust means to realize complex QoE trade-offs for a range of system loads.

Physical layer secrecy performance analysis of multi-user hybrid satellite-terrestrial relay networks

This paper investigates the secrecy performance of a downlink multi-user amplify-and-forward hybrid satellite-terrestrial relay network (HSTRN) with opportunistic scheduling of terrestrial users. By considering Shadowed-Rician fading for satellite link and Nakagami-m fading for terrestrial links, we derive accurate and asymptotic expressions for secrecy outage probability (SOP). Based on the asymptotic behaviour of SOP expression at high signal-to-noise ratio regime, we illustrate practical insights on the achievable diversity order of the system. Subsequently, we also deduce the expression for probability of non-zero secrecy capacity. Finally, numerical and simulation results are provided to vindicate our analysis and to show the impact of various key channel/system parameters such as shadowing severity and number of users on the physical layer secrecy performance of HSTRNs.

Ergodic Capacity of Multiuser Hybrid Satellite-Terrestrial Fixed-Gain AF Relay Networks With CCI and Outdated CSI

In this paper, we investigate the ergodic capacity (EC) of a downlink multiuser hybrid satellite-terrestrial amplify-and-forward relay network (HSTAFRN) using a fixed-gain relaying protocol in the presence of co-channel interference. Herein, we employ opportunistic scheduling of terrestrial users by considering outdated channel state information over Nakagami- m fading channels of pertinent links. By deploying multiple antennas at the satellite, we derive a novel and accurate analytical expression of the achievable EC by making use of the complementary moment generating function transform. More importantly, we carry out the EC analysis under both uncorrelated and correlated shadowed-Rician fading channels of satellite links. Our numerical and simulation results attest the accuracy of the proposed analysis and reveal the impact of various system/channel parameters on EC of the considered HSTAFRN.

Robust optimization for energy-efficient virtual machine consolidation in modern datacenters

Energy efficient virtual machine (VM) consolidation in modern data centers is typically optimized using methods such as Mixed Integer Programming, which typically require precise input to the model. Unfortunately, many parameters are uncertain or very difficult to predict precisely in the real world. As a consequence, a once calculated solution may be highly infeasible in practice. In this paper, we use methods from robust optimization theory in order to quantify the impact of uncertainty in modern data centers. We study the impact of different parameter uncertainties on the energy efficiency and overbooking ratios such as e.g. VM resource demands, migration related overhead or the power consumption model of the servers used. We also show that setting aside additional resource to cope with uncertainty of workload influences the overbooking ration of the servers and the energy consumption. We show that, by using our model, Cloud operators can calculate a more robust migration schedule leading to higher total energy consumption. A more risky operator may well choose a more opportunistic schedule leading to lower energy consumption but also higher risk of SLA violation.

Hybrid Destination-Based Jamming and Opportunistic Scheduling with Optimal Power Allocation to Secure Multiuser Untrusted Relay Networks

In this paper, we investigate secure communication for a dual-hop multiuser relay network, where a source communication with N ( N ≥ 1 ) destinations via an untrusted variable gains relay. To exploit multiuser diversity while protecting source’s confidential message, we first propose a joint destination-based jamming and opportunistic scheduling (DJOS) scheme. Then, we derive closed-form approximated and asymptotic expressions of the secrecy outage probability (SOP) for the considered system with DJOS. Furthermore, we determine an asymptotical optimal power allocation (OPA), which minimizes the asymptotic SOP, to further improve the secrecy performance. Our analytical results show that the achievable secrecy diversity order in terms of SOP with fixed power allocation is min ( 1 , N 2 ) , whereas, with OPA, the achievable secrecy diversity order can be improved up to min ( 1 , 2 N N + 2 ) . This interesting result reveals that OPA can improve the secrecy diversity order of the single-user network. This is intuitive since full diversity order of 1 cannot be achieved when N = 1 , thus leaving some space for OPA to improve the diversity order. Nevertheless, for N ≥ 2 , the effect of OPA is to increase the secrecy array gain rather than the secrecy diversity order since full diversity order 1 has been achieved by the OS scheme. Finally, simulation results are presented to validate our analysis.

A Whittle's Index Based Approach for QoE Optimization in Wireless Networks

The design of schedulers to optimize heterogeneous users' Quality of Experience (QoE) remains a challenging and important problem for wireless systems. This paper explores three inter-related aspects of this problem: 1) non-linear relationships between a user's QoE and flow delays; 2) managing load dependent QoE trade-offs among heterogeneous application classes; and 3), striking a good balance between opportunistic scheduling and greedy QoE optimization. To that end we study downlink schedulers which minimize the expected cost modeled by convex functions of flow delays for users with heterogeneous channel rate variations. The essential features of this challenging problem are modeled as a Markov Decision Process to which we apply Whittle's relaxation, which in turn is shown to be indexable. Based on the Whittle's relaxation we develop a new scheduling policy, Opportunistic Delay Based Index Policy (ODIP). We then prove various structural properties for ODIP which result in closed form expressions for Whittle's indices under different scheduler scenarios. Using extensive simulations we show that ODIP scheduler provides a robust means to realize complex QoE trade-offs for a range of system loads.

Capacity, fairness, and queueing performance analysis of opportunistic scheduling with one-bit feedback

In this paper, we consider opportunistic downlink scheduling in a cellular network that exploits multiuser diversity using one-bit feedback. To reduce the feedback overhead inherent in opportunistic scheduling, mobile stations are allowed to send one-bit information to the base station only when their channel quality exceeds a given threshold value. The objective of this paper is two-fold: (i) find the threshold value that can optimize queueing performance of the scheduler and (ii) investigate the relationship among capacity, fairness, and queueing performance. To this end, we first derive a formula for the sum-rate capacity as a function of the threshold. Next, we quantify the long-term and short-term fairness using Jain’s fairness index. Lastly, we develop a packet-level queueing model and derive QoS measures such as queueing delay and packet loss probability. Based on our analysis, we optimize the threshold value by considering both the traffic condition at the MAC layer and the temporal channel correlation at the PHY layer. Numerical results show that the optimized threshold can significantly reduce the average queueing delay and the packet loss probability. In addition, we find that there is a trade-off between short-term fairness and sum-rate capacity, whose control knob is the threshold. We show that, from a queueing performance perspective, supporting the sum-rate capacity (resp. the short-term fairness) is more important when the traffic is heavy (resp. light) or the wireless channel varies with low (resp. high) temporal correlation.

Revisiting Degrees of Freedom of Full-Duplex Systems with Opportunistic Transmission: An Improved User Scaling Law.

It was recently studied how to achieve the optimal degrees of freedom (DoF) in a multi-antenna full-duplex system with partial channel state information (CSI). In this paper, we revisit the DoF of a multiple-antenna full-duplex system using opportunistic transmission under the partial CSI, in which a full-duplex base station having M transmit antennas and M receive antennas supports a set of half-duplex mobile stations (MSs) having a single antenna each. Assuming no self-interference, we present a new hybrid opportunistic scheduling method that achieves the optimal sum DoF under an improved user scaling law. Unlike the state-of-the-art scheduling method, our method is designed in the sense that the scheduling role between downlink MSs and uplink MSs is well-balanced. It is shown that the optimal sum DoF of is asymptotically achievable provided that the number of MSs scales faster than , where SNR denotes the signal-to-noise ratio. This result reveals that, in our full-duplex system, better performance on the user scaling law can be obtained without extra CSI, compared to the prior work that showed the required user scaling condition (i.e., the minimum number of MSs for guaranteeing the optimal DoF) of . Moreover, the average interference decaying rate is analyzed. Numerical evaluation is performed to not only validate our analysis but also show superiority of the proposed method over the state-of-the-art method.

Strategic Sensing in Vehicular Networks Using Known Mobility Information

In this paper, we study the problem of sensing targets in the context of vehicular networks. First, we define targets to be the vehicles moving on the road and sensors to be the roadside cameras. Then, we study the effect of predicted mobility on reducing the number of times each camera is activated in order to guarantee the coverage of targets. We formulate the sensing problem as an integer linear program using an opportunistic scheduler. Afterward, we extend the formulation and propose a novel strategic scheduler for coverage, which utilizes the predicted mobility information. We then extend this method to a fully distributed version and propose an approximation algorithm by exchanging messages among the sensors. Using a Markovian and a car-following availability models, we show by simulations that the number of activated sensors is significantly reduced by utilizing predicted mobility information. After that, we analyze both schedulers to quantify the gain of utilizing mobility information in sensing. We adopt an independent node mobility model due to its tractability. The analysis is composed of two main components; calculation of mobility gain in terms of sensing cost and probability of feasibility. Our analysis and simulations demonstrate the gain of mobility in sensing targets in terms of higher probability of feasibility and lower sensing cost.

Energy and Bursty Packet Loss Tradeoff Over Fading Channels: A System-Level Model

Energy efficiency and quality of service (QoS) guarantees are the key design goals for the 5G wireless communication systems. In this context, we discuss a multiuser scheduling scheme over fading channels for loss tolerant applications. The loss tolerance of the application is characterized in terms of different parameters that contribute to quality of experience (QoE) for the application. The mobile users are scheduled opportunistically such that a minimum QoS is guaranteed. We propose an opportunistic scheduling scheme and address the cross-layer design framework when channel state information (CSI) is not perfectly available at the transmitter and the receiver. We characterize the system energy as a function of different QoS and channel state estimation error parameters. The optimization problem is formulated using Markov chain framework and solved using stochastic optimization techniques. The results demonstrate that the parameters characterizing the packet loss are tightly coupled and relaxation of one parameter does not benefit the system much if the other constraints are tight. We evaluate the energy-performance tradeoff numerically and show the effect of channel uncertainty on the packet scheduler design.

Exploiting Opportunistic Scheduling for Physical‐Layer Security in Multitwo User NOMA Networks

In this paper, we address the opportunistic scheduling in multitwo user NOMA system consisting of one base station, multinear user, multifar user, and one eavesdropper. To improve the secrecy performance, we propose the users selection scheme, called best‐secure‐near‐user best‐secure‐far‐user (BSNBSF) scheme. The BSNBSF scheme aims to select the best near‐far user pair, whose data transmission is the most robust against the overhearing of an eavesdropper. In order to facilitate the performance analysis of the BSNBSF scheme in terms of secrecy outage performance, we derive the exact closed‐form expression for secrecy outage probability (SOP) of the selected near user and the tight approximated closed‐form expression for SOP of the selected far user, respectively. Additionally, we propose the descent‐based search method to find the optimal values of the power allocation coefficients that can minimize the total secrecy outage probability (TSOP). The developed analyses are corroborated through Monte Carlo simulation. Comparisons with the random‐near‐user random‐far‐user (RNRF) scheme are performed and show that the proposed scheme significantly improves the secrecy performance.

Be Stable and Fair: Robust Data Scheduling for Vehicular Networks

The stable and fair data transmission of vehicular networks can improve transport efficiency and reduce traffic accident. It is challenging to ensure the stability and fairness of data transmission in dynamic vehicular networks. However, existing works based on opportunistic scheduling cannot support reliable transmission since stability and fairness are difficult to be guaranteed at the same time. In this paper, we propose a stable scheduling scheme for dynamic vehicular networks based on fair allocation of available channel resources. We formulate the problem of stability and fairness as network utility maximization, and propose an algorithm, called SF-NUM, to solve it. SF-NUM uses the stability scheduling method based on back pressure vector for the first time in vehicular networks. In order to achieve the fairness distribution of channel resources of the vehicular networks in the distributed computing way, multiple factors are considered in the SF-NUM algorithm. The experimental results show that the proposed algorithm outperforms other algorithms.

Cognitive Relaying Cooperation in Satellite-Terrestrial Systems With Multiuser Diversity

This paper investigates the outage performance of an overlay multiuser hybrid satellite-terrestrial spectrum sharing system. Herein, we exploit both direct and relay links from a primary satellite source to multiple terrestrial users with the coexistence of a secondary transmitter–receiver pair on the ground. Based on an overlay approach, the secondary transmitter provides an amplify-and-forward-based relay cooperation to the primary satellite network that employs opportunistic scheduling of multiple users. The underlying user scheduling strategy is based on satisfying the criterion of minimal outage probability (OP) for the primary network and, eventually, exploring more opportunities of the spectrum sharing for the secondary terrestrial network. By considering the widely adopted Shadowed-Rician fading model for the satellite links while the Nakagami- $m$ fading model for the terrestrial links, we derive the analytical expressions for the OP of the primary satellite network and the secondary terrestrial network and further highlight the corresponding achievable diversity orders. We also examine the impact of power splitting factor for spectrum sharing between primary and secondary networks.

Performance of cooperative multi-hop multiuser relaying networks

This paper presents both capacity and error performances of cooperative multi-hop multiuser relay system. All multi-hop cooperative relays in the system apply maximal-ratio combining (MRC) scheme, while signal transmission to end users is carried out using opportunistic scheduling algorithm. Numerical results for spectral efficiency and average symbol error probability (ASEP) for considered system are presented and discussed.

Secrecy Enhancement of Multiuser MISO Networks Using OSTBC and Artificial Noise

In this paper, we propose a novel physical layer strategy to improve the secrecy performance of multiuser multiple-input single-output networks. In this strategy, orthogonal space-time block code (OSTBC) is employed at an $A_{\text{A}}$ -antenna base station and artificial noise (AN) is employed at an $A_{\text{J}}$ -antenna cooperative relay to enhance the security level of the network. Moreover, two opportunistic scheduling schemes, namely selection combining (SC) and scan-and-wait combining (SWC), are leveraged to select one legitimate user for data transmission. To evaluate the secrecy performance of the proposed OSTBC-SC-AN and OSTBC-SWC-AN schemes, we derive new exact closed-form expressions for the secrecy outage probability and the effective secrecy throughput. Using numerical results, we show that the OSTBC-SWC-AN scheme outperforms the OSTBC-SC-AN scheme when the switching threshold is carefully chosen, while the OSTBC-SC-AN scheme is independent of the switching threshold. We also show that increasing $A_{\text{A}}$ at a low switching threshold or decreasing ${A_{\rm{A}}}$ at a high switching threshold achieves secrecy enhancement for the OSTBC-SWC-AN scheme, while increasing ${A_{\rm{A}}}$ brings better secrecy performance for the OSTBC-SC-AN scheme.

An opportunistic scheduling algorithm using aged CSI in massive MIMO systems

In time-division duplex (TDD) massive multiple-input multiple-output (MIMO) systems, the spatial multiplexing gain cannot be fully achieved since available pilot resources at each channel coherence time interval are limited. In this paper, we propose an Opportunistic user Scheduling algorithm, termed OpSAC, that uses Aged Channel state information (CSI) to increase spatial multiplexing gain without incurring additional pilot overhead. Assuming the base station (BS) employs two popular precoders of maximum ratio transmission (MRT) and zero-forcing (ZF), we first derive their closed-form lower bounds on the achievable sum-rate under channel aging. According to the analysis results, we develop a heuristic solution that estimates the amount of channel variation for each user by using correlation of CSI samples, and exploits channel conditions to opportunistically schedule more users by using aged CSI, thereby enhancing spectral efficiency. Through numerical analysis and simulation we confirm that the proposed lower bounds are very tight, and show the impact of channel aging on the performance of massive MIMO systems. In addition, it is shown that OpSAC achieves near-optimal performance and considerably outperforms the conventional user scheduling algorithm that uses current CSI only.

Performance Analysis of Opportunistic Distributed Scheduling In Multi-User Systems

Consider the problem of a multiple access channel in a time dependent environment with a large number of users. In such a system, mostly due to practical constraints (e.g., decoding complexity), not all users can be scheduled together, and usually only one user may transmit at any given time. Assuming a distributed, opportunistic scheduling algorithm, we analyse the system's properties, such as delay, QoS and capacity scaling laws. Specifically, we start with analyzing the performance while \emph{assuming the users are not necessarily fully backlogged}, focusing on the queueing problem and, especially, on the \emph{strong dependence between the queues}. We first extend a known queueing model by Ephremides and Zhu, to give new results on the convergence of the probability of collision to its average value (as the number of users grows), and hence for the ensuing system performance metrics, such as throughput and delay. This model, however, is limited in the number of users one can analyze. We thus suggest a new model, which is much simpler yet can accurately describes the system behaviour when the number of users is large. We then proceed to the analysis of this system under the assumption of time dependent channels. Specifically, we assume each user experiences a different channel state sequence, expressing different channel fluctuations (specifically, the Gilbert-Elliott model). The system performance under this setting is analysed, along with the channel capacity scaling laws.

Cooperative Internet Access Using Helper Nodes and Opportunistic Scheduling

Having ubiquitous access to the Internet is becoming a necessity of life. Furthermore, we are witnessing a rapid increase in the amount of data requested by mobile users. Cooperative Internet access is a promising approach for addressing these demands, which gives the mobile devices the opportunity to receive help from other mobile devices in order to access the Internet. The helpers can download the data requested by the other users, called clients, through their cellular connections. Then, they transmit the downloaded data to the clients using Wi-Fi or Bluetooth connections. In this paper, we consider the problem of how to share the resources of helpers among a set of clients that request their assistance. Opportunistic scheduling is an effective method that uses the dynamic channel conditions to elevate the systems’ overall utilities. We propose an opportunistic scheduling algorithm in order to efficiently use the helper nodes and share them among the clients fairly. We propose a rate control and scheduling method in the case of using only Wi-Fi connections. We also propose a solution for the case of using Wi-Fi and Bluetooth at the same time. Through simulation results, we show the effectiveness of our cooperative downloading methods.