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This paper proposes a positioning strategy for a fleet of unmanned aerial vehicles (UAVs) airlifting wireless base stations driven by communication constraints. First, two schedulers that model the distribution of resources among users within a single cell are analyzed. Then, an UAV autonomous positioning strategy is developed, based on a fair distribution of the radio resources among all the users of all the cells in a given scenario, in such a way that the user bitrate is the same regardless the users’ distribution and spatial density. Moreover, two realistic constraints are added related to capacity of the backhaul link among the UAVs and the ground station: the bitrate delivered per UAV and the total backhaul bandwidth shared among all the UAVs. Additionally, an energy consumption model is considered to evaluate the efficiency and viability of the proposed strategy. Finally, numerical results in different scenarios are provided to assess both the schedulers performance and the proposed coordinated positioning strategy for the UAVs.

Personalized content retrieval service has become a major information service that consumes a large portion of mobile Internet traffic. Joint content recommendation and delivery is a promising design philosophy that could effectively improve the overall user experience with personalized content retrieval services. Existing research mostly focused on a push-type design paradigm called proactive caching, which, however, has multiple inherent drawbacks such as high device cost and low energy efficiency. This paper proposes a novel, interactive joint content recommendation and delivery system as an alternative to overcome the drawbacks of proactive caching systems. We present several optimal and heuristic algorithms for the proposed system and analyze the system performance in terms of user interest and transmission outage probability. Some theoretical performance bounds of the system are also derived. The effectiveness of the proposed system and algorithms is validated by simulation results.

Due to the high density of vehicles and various types of vehicular services, it is challenging to guarantee the quality of vehicular services in current Long-Term Evolution (LTE) networks in a cost-efficient manner. Fortunately, with the development of fifth-generation (5G) technology, the installation of a large number of small cells is foreseen as one of the practical ways to achieve the low-delay requirement in vehicular environments. However, it may cause a huge operating expense and capital expenditure to mobile network operators due to the limited backhaul capacity and the explosion of signaling. In this paper, we integrate software-defined networking and radio resource virtualization into an LTE system for vehicular networks, i.e., software-defined heterogeneous vehicular network (SERVICE) . Based on this proposed system framework, a delay-optimal virtualized radio resource scheduling scheme is proposed via stochastic learning. The delay optimal problem is formulated as an infinite-horizon average-cost partially observed Markov decision process (POMDP). Then, an equivalent Bellman equation is derived to solve it. The proposed scheme can be divided into two stages, i.e., macro virtualization resource allocation (MaVRA) and micro virtualization resource allocation (MiVRA). The former is executed based on large timescale variables (traffic density), whereas the latter is operated according to short timescale variables (channel state and queue state). Simulation results show that the proposed scheme outperforms traditional schemes. [ABSTRACT FROM PUBLISHER]

The existing works on resource allocation for OFDMA based cognitive radio networks are based on the assumption of Gaussian inputs whereas in practical systems the inputs are taken from a set of finite symbol alphabets. This paper considers a system with arbitrarily distributed finite power inputs and solve the resource allocation problem by employing the relationship between mutual information and minimum mean-square error. To protect the primary users' links, constraint on interference power of the secondary users (SUs) is imposed. In OFDMA based CR networks, a tone can be assigned to one SU at most (exclusivity constraint), due to which the resource allocation problem becomes combinatorial and its solution becomes prohibitively difficult.In this paper, first, the exclusivity constraint on tones allocation is relaxed, the problem is convexified and an optimal solution is derived that provides an upper bound on the system performance. Then, an integer tone allocation and optimal power allocation (ITA-OPA) algorithm is developed that guarantees the assignment of each tone to a single SU with close-to-optimal performance. Finally, keeping in view the complexity of the optimal solution and ITA-OPA algorithm, a low-complexity suboptimal algorithm is devised that accounts for exclusive tone assignment. Simulation results show that the suboptimal algorithm also achieves near-optimal performance. The proposed algorithms outperforms the algorithms that assume Gaussian inputs. [ABSTRACT FROM AUTHOR]

To enable machine type communications (MTCs), MTC gateway (MTCG) is deployed in LTE-A cellular networks. An MTCG can collect data from a group of MTC devices (MTCDs) and forward the data to the base station (BS) via cellular uplinks. This letter proposes a nonorthogonal radio resource allocation (RRA) scheme for MTC-enabled cellular networks, in which an MTCG is configured as a full duplex (FD) relay to assist the uplink transmissions of a group of MTCDs. Through coordinating the transmit powers at the MTCG and MTCDs, the aim of the proposed scheme is to minimize the aggregate energy consumption of the MTCDs while satisfying their delay constraints. The simulation results show that most of the channel reuse gain of FD relaying can be achieved if the self-interference at the MTCG is controlled below a certain level. [ABSTRACT FROM PUBLISHER]

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Most of the existed works on the radio resource allocation (RRA) problem commonly assume the channel-state information (CSI) can be perfectly obtained by the transmission source. However, such assumption is not practical in the realistic wireless systems. In this work, we consider the practical implementation issues of resource allocation in orthogonal frequency division multiple access (OFDMA) two-way relay networks: the inaccuracy of channel-state information (CSI) available to the source. Instead, only the estimated channel status is known by the source. In this context, a joint optimization of subcarrier pairing and allocation, relay selection, and transmit power allocation is formulated in OFDMA two-way amplify-and-forward relay networks. Moreover, the objective of this work is to minimize the energy consumption of the overall system. Further, to ensure the quality of service (QoS) or data rate requirement, the energy consumption must be minimized without compromising the QoS. Therefore, by applying convex optimization techniques, energy-efficient algorithms are developed with the objective to minimize the total transmit power with guaranteeing the required data rates. Through simulation studies, energy consumption performance of the systems under the proposed schemes is investigated. It can be observed that our proposed scheme can improve the energy consumption performance of the considered system. [ABSTRACT FROM AUTHOR]

In this paper, we study radio resource allocation for multicasting in OFDMA based high altitude platforms (HAPs). We formulate and solve an optimization problem that finds the best allocation of HAP resources such as radio power, sub-channels, and time slots. The problem also finds the best possible frequency reuse across the cells that constitute the service area of the HAP. The objective is to maximize the number of user terminals that receive the requested multicast streams in the HAP service area in a given OFDMA frame. A bounding subroutine in a branch and bound algorithm can be obtained by decomposing it into two easier subproblems, due to its high complexity, and solving them iteratively. Subproblem 1 turns out to be a binary integer linear program of no explicitly noticeable structure and therefore Lagrangian relaxation is used to dualize some constraints to get a structure that is easy to solve. Subproblem 2 turns out to be a linear program with a continuous knapsack problem structure. Hence a greedy algorithm is proposed to solve subproblem 2 to optimality. The subgradient method is used to solve for the dual variables in the dual problem to get the tightest bounds. [ABSTRACT FROM PUBLISHER]

Quality of service (QoS) for a network is characterized in terms of various parameters specifying packet delay and loss tolerance requirements for the application. The unpredictable nature of the wireless channel demands for application of certain mechanisms to meet the QoS requirements. Traditionally, medium access control (MAC) and network layers perform these tasks. However, these mechanisms do not take (fading) channel conditions into account. In this paper, we investigate the problem using cross layer techniques where information flow and joint optimization of higher and physical layer is permitted. We propose a scheduling scheme to optimize the energy consumption of a multiuser multi-access system such that QoS constraints in terms of packet loss are fulfilled while the system is able to maximize the advantages emerging from multiuser diversity. Specifically, this work focuses on modeling and analyzing the effects of packet buffering capabilities of the transmitter on the system energy for a packet loss tolerant application. We discuss low complexity schemes which show comparable performance to the proposed scheme. The numerical evaluation reveals useful insights about the coupling effects of different QoS parameters on the system energy consumption and validates our analytical results. [ABSTRACT FROM PUBLISHER]

Orthogonal Frequency Division Multiple Access based 4G cellular systems are designed to support different types of traffic through packet switching only. Hence, packet schedulers are important in increasing Real-Time (RT) traffic capacity as well as non Real-Time (nRT) data throughput of these networks without violating control channel and Quality of Service (QoS) constraints. Increasing capacity and maintaining QoS being conflicting design objectives, a desired Mixed Traffic Scheduler (MTS) algorithm is expected to yield a suitable trade-off between them. In order to identify such an algorithm for any ratio of RT and nRT users in a cell, in this paper, we compare the performance of certain MTS algorithms in terms of number of supportable users, data throughput, control channel usage, and resource usage. We propose two MTS algorithms which treat voice and video as a single traffic class. These are: (1) dynamic packet scheduling and (2) a new limited Joint Time Frequency (JTF) scheduling. These algorithms are compared with known ones like Modified Largest Weighted Delay First (Andrews et al. in IEEE Commun Mag 39(2):150-154, ) and SP-Dynamic (SemiPersistent for VoIP and Dynamic for Video) (Muntean and Otesteanu ). Impact of bundling voice and video packets on the performance of the algorithms is also investigated. Extensive system level simulations show that in addition to 14 video users per MHz, the proposed JTF scheduling with bundled VoIP and video packets can support 57.5 % more VoIP users per MHZ than the 3GPP requirement for only VoIP traffic (ITU-R ). [ABSTRACT FROM AUTHOR]

In future virtual network (VNet) environments, where heterogeneous networks will coexist and new business roles and models are expected, VNets cooperation for radio resource management is one of the key issues in order to achieve an efficient integration of different wireless technologies, while providing the required quality of service. In this paper, an algorithm for Virtual Radio Resource Allocation (VRRA), called OnDemandVRRA, in multiple and heterogeneous virtual networks environment is proposed and discussed. OnDemandVRRA manages the radio resources allocation to the VNets in order to satisfy the VNet contracted capacity. The algorithm has been assessed for two different Virtual scenarios by comparison with a Standard one, in which several network operators have their own networks, each being shared among several mobile virtual network operators. It is shown that the application of OnDemandVRRA to virtualise the wireless access allows achieving better performance from a cluster of several base stations of different radio access technologies, supporting the provision of the contracted capacity for guaranteed VNets, i.e., VNets with a minimum contracted capacity. Globally, it is observed that Virtual scenarios perform better than the Standard one, as the cluster serving data rate may increase by approximately 46 %, if minimum and reference values for the VNet's contracted capacity have been set. Moreover, in this case, end-users performing best-effort services are served with an average data rate approximately three times higher than in other scenarios, where the reference data rate for the VNet providing these services is not set. [ABSTRACT FROM AUTHOR]

In parallel with the amazing increase in mobile data traffic, the fast-growing requirement and development of the green communication technology have led to many energy-saving designs in mobile networks. Meanwhile, as advanced cellular technologies progress, more than one component carrier (CC) can now be jointly utilized in a base station (BS). As a result, the energy consumption of the BS has become an important concern. In this paper, a novel green rate-and-power control transmission scheme is therefore proposed for the BS transmission to address the problem of energy minimization at BS transceivers subject to certain quality-of-service and fairness requirements for all users. Communication activities in downlink transmissions of the BS with orthogonal frequency-division multiple access-based multi-CCs are considered. Simulation results demonstrate that the energy consumption of the proposed novel energy-saving scheme is much better than that of existing schemes, when all schemes satisfy the same constraints. [ABSTRACT FROM PUBLISHER]

This paper considers radio resource allocation (RRA) in the downlink of an orthogonal frequency division multiple access (OFDM)-based spectrum-sharing network. The objective of RRA is to maximize the average achievable throughput subject to the primary service interference threshold and the secondary service transmit power constraint. RRA is usually implemented based on a time window $T$ over which system parameters are averaged and checked against resource constraints. We use short-term ( $T=1$ time slot) and long-term ( $T\gg 1$ slots) averaging as approximations to instantaneous and average constraints, respectively. RRA is also investigated for this system with long-term interference threshold and short-term interference threshold constraints. RRA optimization is a nonconvex optimization problem in which the duality principle is adopted to obtain approximate solutions. The duality gap indicates the degree of approximation in the thus-obtained solution. We prove that the duality gap corresponding to each resource allocation asymptotically decays at least with an exponential rate of $T$. We further show that OFDMA is, asymptotically, the optimal subcarrier assignment. We also propose a practically implementable online power and subcarrier allocation with on-the-fly channel state information measurement. An extensive simulation study has been conducted to verify the theoretically predicted duality gap behavior and to investigate the impact of different system parameters on the secondary service performance. The developed algorithms are also validated to be robust in practical settings and converge fast to theoretical bounds, and thus practically implementable. [ABSTRACT FROM PUBLISHER]

In long term evolution-advanced (LTE-A) networks, the carrier aggregation technique is incorporated for user equipments (UEs) to simultaneously aggregate multiple component carriers (CCs) for achieving higher transmission rate. Many research works for LTE-A systems with carrier aggregation configuration have concentrated on the radio resource management problem for downlink transmission, including mainly CC assignment and packet scheduling. Most previous studies have not considered that the assigned CCs in each UE can be changed. Furthermore, they also have not considered the modulation and coding scheme constraint, as specified in LTE-A standards. Therefore, their proposed schemes may limit the radio resource usage and are not compatible withLTE-A systems. In this paper, we assume that the scheduler can reassign CCs to each UE at each transmission time interval and formulate the downlink radio resource scheduling problem under the modulation and coding scheme constraint, which is proved to be NP-hard. Then, a novel greedy-based scheme is proposed to maximize the system throughput while maintaining proportional fairness of radio resource allocation among all UEs. We show that this scheme can guarantee at least half of the performance of the optimal solution. Simulation results show that our proposed scheme outperforms the schemes in previous studies. [ABSTRACT FROM AUTHOR]

This paper proposes a radio resource allocation algorithm for wireless mesh networks using the orthogonal frequency-division multiple access (OFDMA) technology. We first define the utility function representing user satisfaction in terms of fairness and system throughput. Then, we formulate the optimization problem in which the total system utility is maximized subject to the constraints on the total transmission power, the subcarrier allocation to links, and the amount of data transmitted through a link. A distributed algorithm, which finds a solution to the optimization problem using the Lagrangian relaxation method and the subgradient method, is proposed. The proposed algorithm decides the transmission rates of wireless links, controls data flows to users, and allocates subcarriers to nodes in an optimal and distributive way. We show the performance and accuracy of the proposed algorithm by using simulation. [ABSTRACT FROM AUTHOR]

This study presents a power and Physical Resource Blocks (PRBs) joint allocation algorithm to coordinate uplink (UL) interference in the device-to-device (D2D) underlaying Long Term Evolution-Advanced (LTE-A) networks. The objective is to find a mechanism to mitigate the UL interference between the two subsystems and maximize the weighted sum throughput as well. This optimization problem is formulated as a mixed integer nonlinear programming (MINLP) which is further decomposed into PRBs assignment and transmission power allocation. Specifically, the scenario of applying imperfect channel state information (CSI) is also taken into account in our study. Analysis reveals that the proposed PRBs allocation strategy is energy efficient and it suppresses the interference not only suffered by the LTE-A system but also to the D2D users. In another side, a low-complexity technique is proposed to obtain the optimal power allocation which resides in one of at most three feasible power vectors. Simulations show that the optimal power allocation combined with the proposed PRBs assignment achieves a higher weighted sum throughput as compared to traditional algorithms even when imperfect CSI is utilized. [ABSTRACT FROM AUTHOR]

We consider a wireless system where multiple users are served in Downlink (DL) by one Base Station (BS) and one Relay Station (RS). Previous research has shown that, combining two users' messages via Superposition Coding (SC) could enhance their achievable rate and fairness, in both two-user and multi-user systems. In this work, we propose two novel SC schemes referred as Relayed/Direct (RD-SC) and Relayed/Relayed SC (RR-SC) schemes, that combine the messages to a pair of Relayed/Direct users or Relayed/Relayed users into three or four SC layers, where the number of SC layers is equal to the number of available links. For each scheme, power allocation under sum-rate maximization is analyzed, enabling to derive the optimal power ratios to each SC layer numerically. Then, we design the non-orthogonal Max Rate-Two User-SC (MR-TU-SC) Scheduler and Proportional Fair-Two User-SC (PF-TU-SC) Scheduler where a pair of selected users are allocated simultaneously based on RD-SC and RR-SC schemes. The simulation results show that the proposed schedulers significantly outperform the conventional orthogonal schedulers where a single user is allocated on a unit resource block, in terms of system throughput, fairness and outage, while approaching the upper bound performance. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a new framework to analyze performance considering finite-length queuing and adaptive modulation and coding for multi-user Voice over IP (VoIP) services in wireless communication systems. We formulate an uplink VoIP system as a two-dimensional discrete-time Markov chain (DTMC) based on a Markov modulated Poisson process traffic model for VoIP services and modulation and coding scheme (MCS)-level set transition reflecting users' channel variations. We extend the transition modeling of the MCS-level for a single-user to the transition modeling of the MCS-level set for multiple users. Since the users can have various MCS combinations in the case of a multi-user system, the MCS-level set transitions are more complicated than the MCS-level transitions of the single-user case. Throughout our DTMC formulation, we present various performance metrics, such as average queue-length, average throughput, packet dropping probability, packet loss probability, and so on. By using the results of the packet loss probability, we can find an optimum packet error rate value that minimizes the total packet loss probability. [ABSTRACT FROM AUTHOR]

In this paper, we consider the radio resource allocation problem for uplink orthogonal frequency-division multiple-access (OFDMA) systems. The existing algorithms have been derived under the assumption of Gaussian inputs due to its closed-form expression of mutual information. For the sake of practicality, we consider the system with finite symbol alphabet (FSA) inputs and solve the problem by capitalizing on the recently revealed relationship between mutual information and minimum mean square error (MMSE). We first relax the problem to formulate it as a convex optimization problem, and then, we derive the optimal solution via decomposition methods. The optimal solution serves as an upper bound on the system performance. Due to the complexity of the optimal solution, a low-complexity suboptimal algorithm is proposed. Numerical results show that the presented suboptimal algorithm can achieve performance very close to the optimal solution and that it outperforms the existing suboptimal algorithms. Furthermore, using our proposed algorithm, significant power saving can be achieved in comparison to the case when a Gaussian input is assumed. [ABSTRACT FROM PUBLISHER]

In this paper, we present an energy-per-bit minimized radio resource allocation scheme in heterogeneous networks equipped with multi-homing capability, simultaneously connecting to different wireless interfaces. Specifically, we formulate an optimization problem related to minimization of energy-per-bit which takes a form of nonlinear fractional programming. Then we derive a parametric optimization problem out of that fractional programming and solve the original problem by using a double-loop iteration method. In each iteration, we derive the optimal resource allocation policy by applying Lagrangian duality and an efficient dual update method. In addition, we present suboptimal resource allocation algorithms using the properties of the optimal resource allocation policy. Numerical results reveal that the optimal allocation algorithm improves energy efficiency significantly over the existing resource allocation algorithms designed for homogeneous networks and its performance is superior to suboptimal algorithms in reducing energy consumption as well as in enhancing network energy efficiency. [ABSTRACT FROM PUBLISHER]

In this article, we present a distributed resource and power allocation scheme for multiple-resource wireless cellular networks. The global optimization of multi-cell multi-link resource allocation problem is known to be NP-hard in the general case. We use Gibbs sampling based algorithms to perform a distributed optimization that would lead to the global optimum of the problem. The objective of this article is to show how to use the Gibbs sampling (GS) algorithm and its variant the Metropolis-Hastings (MH) algorithm. We also propose an enhanced method of the MH algorithm, based on a priori known target state distribution, which improves the convergence speed without increasing the complexity. Also, we study different temperature cooling strategies and investigate their impact on the network optimization and convergence speed. Simulation results have also shown the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

A Load and Interference aware Resource Allocation strategy (LIRA) is proposed for multi-radio Wireless Mesh Networks (WMNs), combining multiple mechanisms that efficiently optimise radio resources (rate, power and channel) to guarantee max-min fair capacity to every aggregating Mesh Access Point (MAP). LIRA is composed of a rate adaptation and power control mechanism, sensitive to the fat-tree traffic specificities of WMNs, using the highest bit rates at MAP gateways and using, for the ramified links, the minimum ones that satisfy their capacity needs. This enables to efficiently reduce the transmitted power and interference, advantageous for channel reutilisation. LIRA also integrates a load and interference aware channel assignment mechanism, allowing the simultaneous operation of all links without interference. When this is not achievable, two auxiliary mechanisms of channel sharing and interference-free channel reuse can be sub-sequentially used, reducing the capacity of certain MAPs to guarantee fairness to all nodes. LIRA's gateway flow-control mechanism guarantees that all MAPs respect the allocated capacity, guaranteeing that every MAP is able to operate at its max-min fair capacity. The performance of LIRA is evaluated through simulation, considering IEEE 802.11a. For a classical hexagonal deployment of 19 MAPs with an Internet gateway, it is shown how with only 5 channels LIRA guarantees to every MAP a max-min fair capacity of 3.2 Mbit/s, without packet loss, and delay below 6 ms. It guarantees a max-min fair throughput to every MAP, having a capacity usage efficiency of 66.7 %, an energy efficiency of 26.5 Mbit/J and spectrum efficiency of 0.58 bit/s/Hz. For a more challenging scenario with 27 MAPs and 4 gateways, it is shown how LIRA uses its mechanisms in heterogeneous conditions to also guarantee max-min fair throughput to every MAP, between 5 and 11 Mbit/s, without packet loss, and a delay below 12 ms. Any system improvement will enable to reach higher WMN performance levels using the proposed strategy. [ABSTRACT FROM AUTHOR]

An operational economic model for radio resource allocation in the downlink of a multi-cell WCDMA (acronym for wideband code division multiple access). system is developed in this paper, and a particle swarm optimization (PSO) based approach is proposed for its solution. Firstly, we develop an economic model for resource allocation that considers the utility of the provided service, the acceptance probability of the service by the users and the revenue generated for the network operator. Then, we introduce a constrained hybrid PSO algorithm, called improved hybrid particle swarm optimization (I-HPSO), in order to find feasible solutions to the problem. We compare the performance of the I-HPSO algorithm with those achieved by the original HPSO algorithm and by standard metaheuristic optimization techniques, such as hill climbing, simulated annealing, standard PSO and genetic algorithms. The obtained results indicate that the proposed approach achieves superior performance than the conventional techniques. [ABSTRACT FROM AUTHOR]

In the orthogonal frequency division multiple access (OFDMA) system, one of the efficient and low complex methods to allocate radio resources among multiple users is chunk-based resource allocation, which groups a number of adjacent subcarriers into a chunk and allocates resources chunk by chunk. In this paper, performance analysis of chunk-based resource allocation is studied in the multi-cell OFDMA environment. Fractional frequency reuse (FFR) is considered in the cellular OFDMA. Basically, FFR divides each cell into central and edge areas where two different values of the frequency reuse factor are assumed. This paper analytically evaluates how spectral efficiency performance is affected by system parameters, including radius ratio of the central area to the whole cell, transmit signal to noise ratio (SNR), number of users, number of subcarriers per chunk, and coherence bandwidth. The numerical results show that there exists an optimal radius ratio to achieve the highest spectral efficiency in the proposed research. The optimal radius ratio is about 0.7, which is almost irrespective of the SNR, number of users, and number of subcarriers per chunk. In other words, the sizes of the central area and the edge area of the whole cell are almost equal when achieving the optimal performance. [ABSTRACT FROM AUTHOR]

The radio resource allocation is one of the most important issues to achieve effective wireless communication. In Long Term Evolution (LTE) network, single carrier frequency division multiple access (SC-FDMA) is applied as the transmission technology for uplink traffic. Most researches focus on maximizing the system throughput of SC-FDMA under changeable channel condition. However, users may require different quality of services (QoS) for different applications. This paper studies radio resource allocation for QoS users in localized SC-FDMA system. The proposed scheme divides allocation process into matching algorithm and radio resource assignment algorithm. The Gale-Shapley algorithm is applied to find the optimal matching between resource blocks (RB) and user equipment (UE) by considering channel conditions and the desired QoS. Then the resource assignment algorithm heuristically allocates bandwidth to UE by referring the matched RB under the constraint of carrier continuity. This paper modified the Recursive Maximum Expansion (RME) algorithm to effectively assign radio resource for UEs with different bandwidth demands. The performance of our proposed scheme is compared with the modified RME scheme through exhaustive simulations. The video streaming, VoIP, and FTP traffic types were adopted for simulations. Our simulation results show that the proposed scheme achieves better QoS satisfaction and system throughput than the RME-modified scheme. [ABSTRACT FROM AUTHOR]

The distributed antenna system (DAS) is a promising system to provide high data rate transmissions in wireless communications. So far, most researches in the performance analysis for the DAS have been focused on single-user cases. This paper aims to investigate and present an optimal resource allocation scheme in downlink multiuser DASs. Different from the resource allocation in a conventional cellular system, the resource allocation in the multiuser DAS must consider multiple channel conditions of the transmission links between multiple remote antenna unites (RAUs) and any user, which increases the complexity of the resource allocation. In order to provide insights in the multiuser DAS, the effect of the number of RAUs used to communicate with each user is investigated extensively. In addition to power allocation, subcarrier allocation and bit allocation are studied in the orthogonal frequency division multiple access (OFDMA) DAS. To reduce the complexity of the resource allocation in the downlink multiuser DAS, the chunk allocation technique is adopted by grouping a set of contiguous subcarriers into one chunk and allocating resources chunk by chunk to users and an equivalent channel fading factor per subcarrier for a user is proposed to represent the combined channel gain from multiple RAUs to the user. The numerical results show that by using the proposed resource allocation method, each user only needs to be connected to a few RAUs, depending on the location of the user. [ABSTRACT FROM AUTHOR]

Abstract: A type of joint utility function-based scheduling is proposed for two-way communication services in wireless networks. The scheduling of uplink and downlink services is done jointly so that the base station selects a user efficiently and fairly while considering the channel state of both the uplink and the downlink. Because a user generally has two communication links, an uplink and a downlink, the overall satisfaction with a communication service can be formulated as the sum of the quality of the uplink and downlink services. However, most of the previous types of scheduling for the uplink and downlink were designed separately and independently. This paper proposes a joint scheduling algorithm for integrated uplink and downlink services: a base station selects a user while simultaneously considering both the uplink channel state and the downlink channel state. An analytical model is developed for the purpose of determining the scheduling metric, the system throughput, and the level of fairness. The numerical and computer simulation results show that in comparison with conventional proportional fair scheduling the proposed joint scheduling achieves a better throughput while satisfying the fairness among users. [Copyright &y& Elsevier]

One of the most important challenges in cognitive radio (CR) system is its robustness against primary user jamming problem. Anti-jamming coding mechanism and distributing power properly among subcarriers has been introduced to overcome this problem. In order to increase system performance and secondary network reliability, radio environment information has to be present for designing CR system. In this paper, the erasure probability (Pre,i) for the secondary user receiver is used to select idle subcarriers and to determine the code rate to make a reliable link to transfer secondary user's data. An adaptive coding rate with a proper bit distribution can decrease the negative impacts of primary user's activity, which may be performed better than employing an unpredictable LT code. Furthermore, a multi-level water-filling algorithm is proposed to assign subcarriers' power in coded orthogonal frequency division multiplexing-based CR system. In this algorithm, the interference channel gain is used as a maximum power mask. Simulation results show that the proposed approach can increase the power efficiency and also, at the same time, it reduces the interference on the primary network. [ABSTRACT FROM AUTHOR]

This article presents a comprehensive survey of resource allocation techniques in Wireless Mesh Networks (WMNs). Wireless mesh networks have emerged as a key technology for next generation application specific multi-hop wireless networks. We analyze the state-of-the-art resource allocation schemes for WMNs, providing comprehensive taxonomy of the latest work and the future research trends in this field. In general, the resources that are available for WMNs include time, frequency, space, relays, and power. An efficient utilization of these resources can make the network more robust, reliable, and fair. We categorize the resource allocation into 'radio' resource allocation, 'physical' resource allocation, 'utility' based resource optimization, and 'cross layer' resource optimization. An ample review of resource allocation schemes within these categories is provided. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of resource allocation in a multiple-input multiple-output (MIMO) OFDM-based system, wherein multiple multicast groups exist. Multicasting is a transmission technique which enables a transmitter to communicate via a single wireless link with multiple receivers simultaneously. Moreover, the presence of multiple antennas in both transmitter and receiver enhances significantly the system spectral efficiency. MIMO technology along with multicasting offers major advantages to wireless systems. However, optimum exploitation of these technologies adds significant complexity to the system which makes very difficult any possible practical implementation. Another important issue of such systems is their capacity to ensure to all users a certain level of QoS. To that end, we propose a low complexity fair resource allocation algorithm aiming at ensuring a certain amount of resources to all users when multicasting is applied. Validation of the proposed solution is achieved through extensive simulation and it is compared to other multicast schemes for MIMO systems which exist in literature. Numerical results and complexity analysis show the feasibility of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Heterogeneous wireless networks have emerged as a new paradigm to meet the fast growing wireless network capacity and coverage demands. Due to the co-deployment of high power and low power nodes in the same network using the same spectrum, more advanced interference coordination and radio resource management schemes are required than in the traditional cellular network in order to achieve a high network capacity and good user experience. In this paper, we propose an optimal fractional frequency reuse and power control scheme that can effectively coordinate the interference among high power and low power nodes. The scheme can be optimized to maximize the sum of the long term log-scale throughput among all the user equipments (UEs). Towards that end, the Lagrange dual function is first derived for the proposed optimization problem. Gradient descent method is then used to search the optimal solution for the convex dual problem. Due to the strong duality condition, the optimal solution for the dual problem is also the optimal solution for the primal problem. Simulation results show that the proposed scheme can greatly improve the wireless heterogeneous network performance on system capacity and user experience. [ABSTRACT FROM PUBLISHER]

The enhancement of cellular networks with relaying technologies is expected to bring significant technoeconomic benefits at the expense of more complex resource allocation. Suitable models for solving network dimensioning problems in cellular-relaying networks must handle radio resource allocation among hundreds of links and tackle interactions between networking layers. For this purpose, we propose a novel cross-layer resource allocation model based on average interference and ideal rate adaptation for the physical layer (PHY), time shares for the medium access layer, and fluid flows for the transport and network layers. We formulate a centralized social welfare maximization problem. When the routes are selected with an a priori algorithm, we show that the resource allocation problem admits an equivalent convex formulation. We show a numerical example for how to use the proposed framework for configuring the backhaul link in a practical relaying network. The overall problem of selecting routes and allocating time shares and link rates is nonconvex. We propose an iterative suboptimal algorithm to solve the problem based on a novel approximation of PHY. We state and prove several convergence properties of the algorithm and show that it typically outperforms routing based on signal-to-noise ratio only. [ABSTRACT FROM PUBLISHER]

This paper considers the problem of radio resource allocation in an orthogonal frequency-division multiple access based cognitive radio (CR) network that opportunistically operates within the licensed primary users (PUs) spectrum. The resource allocation algorithm aims at maximizing the CR network throughput under PUs interference constraints. The CR interference introduced into PUs subbands is modeled as a composite that consists of the following two parts: 1) CR out-of-band emissions and 2) the interference that arises as a result of imperfect spectrum sensing. We consider both downlink and uplink subcarrier and power allocation. In both cases, the resource allocation problem is a mixed-integer nonlinear programming problem, for which obtaining the optimal solution is known to be \cal N\cal P-hard. Computationally efficient suboptimal algorithms are proposed for the downlink resource allocation problem, and then, they are extended to the uplink case. We show through simulation that the proposed algorithms exhibit near-optimal performance and significantly reduce the computational complexity compared to obtaining the optimal solution. [ABSTRACT FROM PUBLISHER]