Uplink Resource Allocation Research Articles

Queue-aware uplink scheduling with stochastic guarantees

Adaptive resource allocation arises naturally as a technique to optimize resource utilization in communication networks with scarce resources under dynamic conditions. One prominent example is cellular communication where service providers seek to utilize the costly resources in the most effective way. In this work, we investigate an uplink resource allocation scheme that takes into account the buffer occupation at the transmitter to retain a given level of quality of service (QoS). First, we regard exact results for the class of Poisson traffic where we investigate the sensitivity of the resource adaptation and QoS level to the actuating variables. We show relevant resource savings in comparison with a static allocation. Further, we regard a queueing setting with general random arrival and service processes. In particular, we consider the service of wireless fading channels. We show two different resource adaptation mechanisms that depend on the strictness of different assumptions. Finally, we present simulation results that show substantial resource savings using the queue-aware scheduling scheme, where we provide insight on the implementation and operation of such an adaptive system.

Differentiating and Scheduling LTE Uplink Traffic Based on Exponentially Weighted Moving Average of Data Rate

The importance of uplink resource allocation in ensuring the Quality of Service (QoS) of guaranteed bit rate (GBR) bearers has led to the development of numerous resource allocation schemes. The criteria used in the development of such schemes include maximizing system throughput or fairness and the ability to take transmission power or user priority into account. After accepting a GBR bearer, the eNodeB (eNB) must allocate sufficient resource blocks (RBs) to guarantee the requested QoS. In order to achieve high utilization of radio resource, eNB also must allocate remaining RBs to non-GBR bearers. The QoS is generally specified by the data rate (throughput) or packet delay; however, the 3rd Generation Partnership Project (3GPP) has not specified the means by which data rates for a GBR bearer are to be measured. In this paper, we define the measurement of data rates based on the exponentially weighted moving average (EWMA), thereby enabling the eNB to perform scheduling tasks with greater accuracy. We also present an AAG-2 (Allocate As Granted-version 2) scheme capable of supporting the QoS for GBR bearers, while enabling the efficient allocation of RBs to non-GBR bearers. The existence of parties seeking superior levels of service makes it necessary for telecommunications operators to provide options with regard to QoS. This study proposes a revision of the AAG-2 scheme referred to as AAG-D to accommodate such demands. Simulation results demonstrate the efficacy of the new scheme in achieving goals related to throughput and average packet delay.

Multimedia Sensing as a Service (MSaaS): Exploring Resource Saving Potentials of at Cloud-Edge IoTs and Fogs

With the popularity of multimedia sensing at cloud edges and the reducing cost of the Internet of Things (IoT) fog devices and systems, new challenges have been posed to efficiently deal with the big data multimedia traffic generated from IoT sensing units. Specifically, in this paper we introduce the concept of multimedia sensing as a service (MSaaS), and propose a generalized premium prioritization-based quality of experience paradigm for wireless big-volumes-of-data (BVDs) multimedia communications, with significant energy saving potentials for future multimedia IoT devices and systems. The key contribution of this new framework is its data diversity flexibility at the application layer, which could be flexibly adopted by future multimedia communication systems. Data dependencies in spatial, frequency and temporal domains are analyzed, and interaction with uplink resource allocation optimization are investigated with regards to wireless communication energy cost estimation. Extensive simulation results demonstrate that the proposed prioritization-based communication paradigm has significant energy saving potentials for BVD MSaaS wireless multimedia communications at cloud edges and fogs.

Uplink resource allocation in SC-FDMA wireless networks: A survey and taxonomy

SC-FDMA has been selected by the Third Generation Partnership Project (3GPP) Long Term Evolution (LTE) and LTE Advanced (LTE-A), as the primary multiple access scheme for the uplink of the 4 G wireless communication systems. This article surveys the different state-of-the-art resource allocation algorithms developed to allocate system's subcarriers and users’ transmission powers in the uplink of SC-FDMA wireless networks. An objective-driven classification approach is followed where the various resource allocation algorithms are categorized into four major classes based on the ultimate goal/objective of the resource allocation process, as follows: (i) throughput optimization, (ii) fairness, (iii) satisfaction of users’ QoS requirements, and (iv) joint power and subcarriers allocation. The article summarizes the activities and recent advances on this work-in-progress area, highlights the key features, advantages and disadvantages of each algorithm, and provides a detailed qualitative comparative evaluation of their attributes and characteristics according to several distinct features. Furthermore, it provides some indicative numerical results that better present and quantify the objective and achieved performance of the various algorithms. Finally the problem of resource allocation is discussed, when multicell environment is considered, where issues such as intercell interference mitigation and backhaul rate constraints pose additional challenges.

Uplink Co-Tier Interference Management in Femtocell Networks With Successive Group Decoding

We propose a new scheme to mitigate the uplink co-tier interference in dense femtocell networks, assuming that advanced receivers are employed by the femtocell base stations (FBSs). The conventional solution where interfering cells are assigned orthogonal spectrum resources leads to the inefficient spectrum usage. We exploit resource reuse by taking advantage of the successive group decoder (SGD) such that users can opportunistically access the entitled resources of nearby cells. The SGD decodes some interference signals in order to best decode the useful signal. Multi-cell uplink resource allocation with SGDs is formulated as a joint channel, rate and decoding group (CRG) allocation problem to maximize the weighted sum rates of the variable bit rate (VBR) users while meeting the rate requirements of the guaranteed bit rate (GBR) users. Due to the provable NP-hardness of the problem, we propose a greedy algorithm where the idea is to let GBR users opportunistically transmit on the channels of nearby cells and release more interference-free channels for high-rate transmission of VBR users. A semi-analytical framework is developed to provide a rough estimate of the potential throughput gain by the proposed technique. Simulation results show that the throughput gain over the conventional orthogonal resource allocation ranges from 10%–140% with different traffic proportion, number of users and rate requirement.

Joint Downlink and Uplink Resource Allocation for Energy-Efficient Carrier Aggregation

In this paper, joint energy-efficient resource allocation for both the base station and users is studied for time division duplex (TDD) systems with carrier aggregation (CA). We aim at balancing the energy efficiency (EE) between downlink and uplink, as well as the EEs among individual users, by joint bandwidth and power allocation on each carrier component (CC). We formulate the optimization problem into maximizing the weighted summation of EEs for the base station and different users, where the weights are used to reflect the levels of importance. The objective function of the problem is a sum of several fractional functions, therefore, nonlinear sum-of-ratios programming needs to be used to solve it, which has not been exploited in resource allocation problems yet. Specifically, a novel transformation is performed to formulate an equivalent but better tractable problem, based on which we develop an iterative algorithm to find the global optimum of the considered problem. Numerical results validate the feasibility, fast convergence, and flexibility of the proposed algorithm in terms of EE balancing.

Primary user localisation and uplink resource allocation in orthogonal frequency division multiple access cognitive radio systems

In cognitive radio networks, secondary users (SUs) can share spectrum with primary users (PUs) under the condition that no interference is caused to the PUs. To evaluate the interference imposed to the PUs, the cognitive systems discussed in the literature usually assume that the channel state information (CSI) of the link from a secondary transmitter to a primary receiver (interference link) is known at the secondary transmitter. However, this assumption may often be impractical in cognitive radio systems, since the PUs need to be oblivious to the presence of the SUs. The authors first discuss PU localisation and then introduce an uplink resource allocation algorithm for orthogonal frequency division multiple access-based cognitive radio systems, where relative location information between primary and SUs is used instead of CSI of the interference link to estimate the interference. Numerical and simulation results show that it is indeed effective to use location information as a part of resource allocation and thus a near-optimal capacity is achieved.

Spectrum Refarming: A New Paradigm of Spectrum Sharing for Cellular Networks

Spectrum refarming (SR) refers to a radio resource management technique which supports different generations of cellular networks to operate in the same radio spectrum. In this paper, an underlay SR model is proposed for an Orthogonal Frequency Division Multiple Access (OFDMA) system to share the spectrum of a Code Division Multiple Access (CDMA) system through intelligently exploiting the interference margin provided by the CDMA system when operating with a low system load. The asymptotic signal-to-interference-plus-noise ratio (SINR) of the CDMA system is used to quantify the interference margin, which interestingly does not depend on the instantaneous information (spreading codes and channel state information) of the CDMA system, thanks to its internal power control. By using the transmit power constraints together with the derived interference margin, the uplink resource allocation problem for OFDMA system is formulated and solved through dual decomposition method. The proposed SR system only requires high level system parameters from the CDMA system, hence, the upgrading of legacy CDMA system is not needed. Simulation results have verified our theoretical analysis, and validated the effectiveness of the proposed resource allocation algorithm and its capability to protect the legacy CDMA users.

Radio resource management for uplink carrier aggregation in LTE-Advanced

This paper investigates the uplink resource allocation problem in the context of Long-Term Evolution (LTE)-Advanced systems with carrier aggregation (CA) and dual-cluster scheduling. On one hand, these Rel’10 functionalities can increase the available transmission bandwidth and scheduling flexibility in uplink. On the other hand, they will introduce additional power back-off for the power amplifier in the user equipment (UE) with non-contiguous resource allocation. Taking into account that the uplink is inherently limited by the maximum transmission power of the UE, the assignment of uplink CA and/or dual cluster transmission for LTE-Advanced UEs has to be careful. A pathloss-threshold-based component carrier (CC) and cluster configuration algorithm is proposed to determine whether an LTE-Advanced UE should be configured with multiple CCs and/or dual cluster scheduling. An extended bandwidth-expansion-based packet scheduling algorithm is proposed for dual-cluster transmission, which tightly couples the bandwidth allocation and packet scheduling together to exploit the frequency domain diversity with low complexity. Simulation results show that with proper differentiation between power-limited and non-power-limited UEs, Rel’10 CA with dual-cluster scheduling can maintain similar coverage performance as in Rel'8 case while achieving substantial gains in median and peak user throughputs. Moreover, the proposed CC assignment algorithm achieves higher user throughput as compared to blindly assigning all UEs on all available CCs.

LTE uplink interference aware resource allocation

In this paper, we investigate a multi-cell Long Term Evolution (LTE) uplink resource allocation problem by mitigating the inter-cell interference based on interference graph, in which the vertices represent the user equipments (UEs) and the edges represent interference relations between the UEs. We derive two different interference graphs based on the cellular channel statistics, namely, the enhanced interference graph (EIG) and simplified interference graph (SIG). For EIG, the edge between two UEs is associated with the weight value related to the interference state between them; whereas for SIG, the edge between two UEs exists only when they interfere with each other. Given that the LTE uplink resource allocation is NP-hard, heuristic algorithms are proposed based on EIG and SIG, respectively, to give solutions with reasonable complexity. The system-level simulation results show that all the algorithms can mitigate the inter-cell interference significantly. EIG-based algorithm has the better fairness relative to SIG-based algorithms, however SIG-based algorithms are preferred in terms of throughput, complexity, and overhead.

Energy efficiency‐based device‐to‐device uplink resource allocation with multiple resource reusing

Device-to-device communication fulfils its potential in terms of high resource utilisation, thus it has been a hot topic in the recent long-term evolution standardisation process. The general scenario with multiple resource pool multiplexing instead of the one-time reusing is considered. Meanwhile, the optimisation target focuses on device energy efficiency under certain system throughput insurance rather than the traditional system throughput. A modified genetic algorithm-based scheme is applied to address the facing non-deterministic polynomial-time hard problem with higher convergence and lower complexity.

Context-Aware Uplink Resource Allocation Using Request Header Information for ertPS Services in IEEE 802.16e Networks

In this paper, we propose a simple and effective way to improve the quality of service (QoS) of uplink resource allocation for the extended-real-time polling service (ertPS) in IEEE 802.16e broadband wireless networks. The primitive ertPS algorithm determines the amount of resources allocated to a given subscriber station only according to the requested volume in current polling cycles regardless of the knowledge of demand trend. This trend is continuously increasing or declining, which may be incomplete to truly reflect reasonable resource allocation for subscriber stations in different demand tendencies. To cope with this problem, we developed a context-aware ertPS algorithm which gathers statistics on the numbers of request headers of medium access control layer management messages among various subscriber stations, and thus uses the statistical information to enable a dynamic allocation of additional uplink resources to subscriber stations with continuously increasing bandwidth demands. The simulation results show that in comparison with the original ertPS algorithm, the proposed context-aware resource allocation scheme is effective to increase the data throughput as well as to decrease the packet loss rate and packet delay so that the user-perceived QoS can be improved.

Secure Robust Ergodic Uplink Resource Allocation in Relay-Assisted Cognitive Radio Networks

We investigate the ergodic uplink resource allocation problem for secure communication in relay-assisted orthogonal frequency-division multiple access (OFDMA)-based cognitive radio networks (CRNs) in the presence of a set of passive eavesdroppers where relay nodes assist the legitimate users to transmit their messages. Previous works have commonly assumed the availability of channel state information (CSI) for this type of problems. However, due to the decentralized nature of CRNs and hidden activities of eavesdroppers, the assumption of availability of exact values of CSI is not realistic. In this paper, we consider uncertainty on the estimated values of CSI between different transmitters and receivers, e.g., CSI between each legitimate transmitter and its corresponding receiver and CSI of each legitimate user and each eavesdropper. We utilize the worst-case robust formulation to find power and sub-carrier allocations in such a way that under the worst condition of error, the regulatory constraints imposed to CRN are satisfied and the secrecy rate of each secondary legitimate user is stabilized. It is well known that the robust approaches impose a high computational complexity to the system and reduce the system performance as they conservatively consider the error in the maximum extent. We demonstrate how the robust formulation can be significantly simplified and tradeoff parameters can be introduced to moderate the effect of the worst-case approach. Simulation results are provided to demonstrate the performance of CRNs for different uncertain system parameters.

Uplink spectrum resource allocation in heterogeneous networks (small cell/macrocell)

Small cells are expected to increase network capacity, extend the macrocell coverage and to add edge-based intelligence. These advantages are achieved by overlaying macrocell networks with the small cells, resulting in a two-tier network. However, the average capacity of the network is reduced due to interference generated by the two-tier configuration. Conventional small cells are configured to have either an open or closed access scheme. Small cells with a hybrid access scheme or partially open access scheme are known for their flexibility and improved performance achieved through their interference-mitigating ability and adaptive resource allocation capabilities. In a hybrid access scheme, resource allocation is a vital issue in the design of small cells networks. In this paper, we propose an uplink resource allocation technique to enhance hybrid small cell capacity in orthogonal frequency division multiple access (OFDMA) two-tier cellular networks. In particular, we investigate a new possibility available for developing an optimal scheme for OFDMA hybrid access small cells. We formalize the problem as an optimization problem for an uplink resource allocation that partitions the bandwidth for both subscribed or unsubscribed users. Moreover, we propose a convex optimization model for the gradient of the capacity difference between closed access and hybrid access capacity. We present two schemes, firstly an optimal scheme and secondly a scheme that is the simple version of the optimal scheme. Numerical results show the effectiveness of the proposed bandwidth resource allocation, where the simple solution shows inferior performance than the optimal solution with a small margin while the optimal solution has a more mathematical complexity disadvantage due to the mathematical functions it employs. Numerical results also show the convergence and effectiveness of the proposed uplink bandwidth resource allocation scheme.

Design a Cross-layer Uplink Green Resource and Power Allocation Method over LTE-A Relay Network

The Relay Node (RN) in Long-Term Evolution-Advanced (LTE-A) networks is used to enhance the coverage of high data rate and solve the coverage hole problem. However, for User Equipments (UEs), using a higher transmission rate means more energy consumption; especially they are operated by batteries. In this paper, we consider an uplink resource and power allocation problem for energy conservation in LTE-A relay networks. The objective is to minimize the total energy consumption of UEs while guarantee their quality of services (QoSs). We prove that this uplink resource and power allocation problem to be NP-complete and we develop a method to solve the problem. Simulation results show that our algorithm can effectively reduce the energy consumption and guarant ee users' service quality.

Adaptive Resource Allocation for MC-CDMA and OFDMA in Reconfigurable Radio Systems

This paper studies the uplink resource allocation for multiple radio access (MRA) in reconfigurable radio systems, where multiple-input and multiple-output (MIMO) multicarrier-code division multiple access (MC-CDMA) and MIMO orthogonal frequency-division multiple access (OFDMA) networks coexist. By assuming multi-radio user equipment with network-guided operation, the optimal resource allocation for MRA is analyzed as a cross-layer optimization framework with and without fairness consideration to maximize the uplink sum-rate capacity. Numerical results reveal that parallel MRA, which uses MC-CDMA and OFDMA networks concurrently, outperforms the performance of each MC-CDMA and OFDMA network by exploiting the multiuser selection diversity.

Improved OFDMA Uplink Resource Allocation Algorithm Based on Message Passing

A distributed subchannel assignment scheme for OFDMA uplinks via batchwise message passing (MP) is proposed. Each batch of iterations completes partial allocation of subchannels resulting in partial withdrawal of the subchannels and users. This saves the subsequent consumption of message and speeds up its updates. Moreover, the modification of Hoare's FIND (HF) algorithm gains a further speedup of updates of the message. An average computation speedup of around 3x and message saving of nearly 20% over SF-MP scheme is achieved.

Joint allocation of uplink and downlink resources for interactive mobile cloud applications

AbstractCloud‐based mobile applications are interactive in nature. Due to the strong correlation between uplink request and downlink response, it is irrational to optimize the uplink and downlink resource allocation problem separately and independently. In this paper, the joint uplink and downlink resource allocation problem for interactive mobile cloud applications is considered. The data exchange characteristics between mobile terminal and cloud server is investigated and a novel traffic model including both uplink and downlink transmission queues is constructed. Based on the new traffic model, the resource allocation problem can be formulated as a constrained Markov Decision Process. The objective is to minimize the application response time, that is, the roundtrip delay of causally related packet group (PG) pairs, with a constraint on PG drop rate. The Q‐learning algorithm and Value Iteration Algorithm are employed to obtain a solution that converges to the optimal one. To combat the curse of dimensionality, a sub‐optimal solution is proposed to solve the problem with an acceptable complexity. Numerical results indicate that the reduced complexity solution can achieve a delay performance approximate to that of the optimal solution and outperform other allocation schemes. Copyright © 2014 John Wiley & Sons, Ltd.

Resource Management and QoS Provisioning for Duplex Services in IEEE 802.16

Duplex services are multimedia services that requires good connectivity in both uplink and downlink such as VoIP, video conferencing and interactive gaming. A weak connection in either direction may cause degradation of performances and dissatisfaction of user experience. Most researchers do not consider this issue and treat resource allocations in uplink and downlink independently. For this reason, the conventional resource management schemes do not guarantee a good duplex connectivity. Generally, duplex schemes require some relation or information to be exchanged between uplink and downlink resource allocation processes. The existing duplex resource allocation schemes, however, have high complexity and do not adhere to the IEEE 802.16 standard. In this paper, we propose a duplex resource management scheme for IEEE 802.16 network to enhance the user experience and to improve the network performances. The proposed resource management scheme is a MAC layer function that co-relates the uplink and downlink allocation processes using a newly proposed duplex variable. Simulation studies show that the proposed scheme brings significant benefit to duplex services in the IEEE 802.16 networks and outperforms the conventional and existing schemes in terms of uplink and downlink transmission gap, QoS performances and fairness.

Two Time-Scale Cross-Layer Scheduling for Cellular/WLAN Interworking

In this paper, we investigate uplink resource allocation for wireless local area network and cellular network interworking to provide multi-homing voice and data services. The problem is formulated based on the physical layer and medium access control layer technologies of the two networks to ensure that the resource allocation decisions are feasible and can be executed at the lower layers. Furthermore, to efficiently utilize users' equipment (UEs) battery power, the power distribution among multiple network interfaces of the UEs is included in the problem formulation. The optimal resource allocation problem is a multiple time-scale Markov decision process (MMDP) as the two networks operate at different time-scales and due to voice and data service requirements. We derive decision policies for the upper and the lower levels of the MMDP by decomposing each resource allocation problem over multiple time slots to a set of resource allocation problems for individual time slots and solving the resource allocation problems corresponding to individual time slots using convex optimization techniques. To reduce the time complexity, we further propose a heuristic resource allocation algorithm by deriving the decision policies based on a single system state. The system state consists of average square channel gains for dual variable calculation and instantaneous channel gains for resource allocation based on the calculated dual variables. Simulation results demonstrate the achievable throughput and service quality improvements by employing these two algorithms.