Dynamic Radio Resource Management Research Articles

Dynamic Power Allocation in High Throughput Satellite Communications: A Two-Stage Advanced Heuristic Learning Approach

The dynamic radio resource management technology is an essential technology in high throughput satellite (HTS) communications. Aiming at the problem that the traditional static radio resource allocation is difficult to meet the dynamic traffic, the dynamic radio resource allocation based on the meta-heuristic algorithm has been extensively studied. Since wireless channel conditions, differentiated services have stochastic properties, and the environment's dynamics are unknown in HTS, the dynamic radio resource allocation based on model-free deep reinforcement learning (DRL) method was used to learn the optimal policy through interactions with the situation. However, the generalization ability of the existing DRL cannot fully meet the great dynamic change in HTS. To address this issue, we explore an advanced heuristic learning approach that combines DRL with one heuristic algorithm. In the proposed approach, we apply the DRL to accelerate the convergence of the heuristic algorithm and verify the proposed method in the dynamic power allocation (DPA) in HTS. Compared with the traditional methods, the simulation results show that the proposed approach can accelerate the convergence of the heuristic method for the allocation of power in HTS and has a low time complexity of the decision. Compared with the traditional methods, our proposed method can reduce the computational overhead by 6.2-94.8%.

Toward Safe and Accelerated Deep Reinforcement Learning for Next-Generation Wireless Networks

Deep reinforcement learning (DRL) algorithms have recently gained wide attention in the wireless networks domain. They are considered promising approaches for solving dynamic radio resource management (RRM) problems in next-generation networks. Given their capabilities to build an approximate and continuously updated model of the wireless network environments, DRL algorithms can deal with the multifaceted complexity of such environments. Nevertheless, several challenges hinder the practical adoption of DRL in commercial networks. In this article, we first discuss two key practical challenges that are faced but rarely tackled when developing DRL-based RRM solutions. We argue that it is inevitable to address these DRL-related challenges for DRL to find its way to RRM commercial solutions. In particular, we discuss the need to have safe and accelerated DRL-based RRM solutions that mitigate the slow convergence and performance instability exhibited by DRL algorithms. We then review and categorize the main approaches used in the RRM domain to develop safe and accelerated DRL-based solutions. Finally, a case study is conducted to demonstrate the importance of having safe and accelerated DRL-based RRM solutions. We employ multiple variants of transfer learning (TL) techniques to accelerate the convergence of intelligent radio access network (RAN) slicing DRL-based controllers. We also propose a hybrid TL-based approach and sigmoid function-based rewards as examples of safe exploration in DRL-based RAN slicing.

A NURBS-optimized dRRM solution in a mono-channel condition for IEEE 802.11 entreprise Wlan networks

Dynamic radio resource management, RRM, is an essential design block in the functional architecture of any Wifi controller in IEEE 802.11 indoor dense enterprise Wlans. In a mono-channel condition, it helps tackle co-channel interference problem and enrich end-to-end Wifi clients experience. In this work, we present our dRRM solution: WLCx, and demonstrate its performance over related-work and vendor approaches. Our solution is built on a novel and realistic per-Beam coverage representation approach. Unlike the other RRM solutions, WLCx is dynamic: even the calculation system parameters are processed. This processing comes at price in terms of processing time. To overcome this limitation, we constructed and implemented a NURBS surface-based optimization to our RRM solution. Our NURBS optimized WLCx, N-WLCx, solution achieves almost 92.58% time reduction in comparison with basic WLCx. Furthermore, our optimization could easily be extended to enhance others, vendors and research, RRM solutions.

Optimal distributed power control in wireless cellular network based on mixed Kalman/[formula omitted] filtering

In any wireless cellular network, power control is one of the most important dynamic radio resource management (RRM) schemes which increases the capacity and performance of the system. In this paper, we present a modified scheme to Distributed Power control that optimize the transmission power of mobile’s and signal-to-interference-plus-noise ratio (SINR) error. This method, based on minimization of performance criterion, achieves the minimum SINR error and power consumption at the next time instant. The Mixed Kalman/H∞ Filter with covariance intersection has been applied in the proposed scheme to estimate and predict the channel variation and still ensure a good robustness. Finally, the mixed Kalman/H∞ filter based power control method is compared with Kalman filter and H∞ filter based power control results show that our method provides robustness against practical impairments, such as measurement uncertainties and fast channel variations.

Cross‐layer capacity optimisation in WiMAX orthogonal frequency division multiple access systems with multi‐class quality of services and users queue status

Given the broad range of applications supported, high data rate required and low latency promised; dynamic radio resource management is becoming vital for the air interface technologies such as WiMAX and LTE adopted by international standards. This study considers the OFDMA system, which has been implemented in both WiMAX and LTE technologies as their air interface multiple access mechanism. A framework for optimised resource allocation with QoS support that aims to balance between service provider's revenue and subscriber's satisfaction is proposed in this study. A cross-layer optimisation design for subchannel and power allocations with the objective of maximising the capacity (in bits/symbol/Hz) subject to fairness parameters and QoS requirements as constraints is presented. The optimisation does not only consider users channel conditions but also queue status of each user as well as different QoS requirements. The QoS classes adopted by the IEEE 802.16e standard, for WiMAX technology, are utilised in this study. In the proposed framework, the problem of power allocation is solved analytically whereas the subchannel allocation is solved using integer programming exhaustive search. The simulation and numerical results obtained in this study have shown improved system performance as compared to other optimisation schemes known in the literature.

Traffic characteristics based dynamic radio resource management in heterogeneous wireless networks

The traffic with tidal phenomenon in Heterogeneous Wireless Networks (HWNs) has radically increased the complexity of radio resource management and its performance analysis. In this paper, a Simplified Dynamic Hierarchy Resource Management (SDHRM) algorithm exploiting the resources dynamically and intelligently is proposed with the consideration of tidal traffic. In network-level resource allocation, the proposed algorithm first adopts wavelet neural network to forecast the traffic of each sub-area and then allocates the resources to those sub-areas to maximise the network utility. In connection-level network selection, based on the above resource allocation and the pre-defined QoS requirement, three typical network selection policies are provided to assign traffic flow to the most appropriate network. Furthermore, based on multidimensional Markov model, we analyse the performance of SDHRM in HWNs with heavy tailed traffic. Numerical results show that our theoretical values coincide with the simulation results and the SDHRM can improve the resource utilization.

Dynamic radio resource and interference management for MIMO–OFDMA mobile broadband wireless access systems

A multi-user multi-cell Multiple-Input Multiple Output/Orthogonal Frequency Division Multiple Access (MIMO/OFDMA) system for next generation Broadband Wireless Access (BWA) networks is studied, in which the Base Station (BS) or evolved Node B (eNB) has only knowledge of the statistics of the channel. A combination of MIMO and OFDMA could increase the spectral efficiency in a high speed network. We investigate methods with scalable channel feedback and we analyze the trade off between the amount of Channel State Information (CSI) to the transmitter and the system performance. The proposed schemes with limited feedback are combined with other cell interference reduction strategies based on cooperation for improving the performance of a coordinated multi-cell system under very dynamic conditions like high velocity and fast fading. Simulation results demonstrate that substantial gain is obtained by the proposed schemes which take advantage of the statistical information of the highly dynamic channel.

Cognitive control channels: from concept to identification of implementation options

Recent effort related to cognitive radio systems has lead to an in-depth analysis of context information management and exploitation based on a cognitive control channel for enhancement of management needed for, say, suitable link selection in a heterogeneous radio framework, dynamic radio resource management, and distributed sensing. Concerning the actual implementation of such a CCC, the focus was recently moved toward an in-band solution, where the information is transported building on existing radio access technologies. In this scope, this article illustrates relevant technical scenarios in which CCCs can be exploited and outlines a set of derived system requirements. The article provides an overview of various possible RAT independent and dependent implementation options, such as Diameter, distributed agents, 3GPP radio resource control (RRC) mechanisms, IEEE 802.21, IEEE 802.11, WiMedia UWB, and Bluetooth. The advantages and drawbacks of the various options are discussed.

A dynamic radio resource management scheme for the IEEE 802.16 band‐adaptive modulation and coding mode with proportional rate constraints

ABSTRACTIn this paper, we consider the problem of downlink resource allocation in the IEEE 802.16 standard based on the orthogonal frequency‐division multiple access physical layer. The objective is to allocate the downlink frequency‐time slots and transmission power to different users such that the total throughput is maximized. The allocation is subject to constraints on the total transmission power and satisfying the quality of service requirements of different users expressed in terms of proportional rates. A three‐step heuristic scheme that incorporates a linear programming technique is proposed. The problem is modelled as an unbalanced transportation problem that is solved to obtain the users' slot assignment. The Vogel approximation method is used to efficiently solve the transportation problem with a slight degradation relative to the optimal solution. The Vogel approximation method gain is shown by replacing it in the three‐step heuristic by simple round‐robin or greedy slot assignment. In terms of total throughput and fairness, it is shown that the proposed scheme is a good compromise between the greedy‐oriented schemes, which aspire to maximize the total system throughput but sacrificing fairness, and a proportional rate constraints scheme introduced in the literature that achieved short‐term fairness but penalizes the total throughput. The study also shows that the proposed scheme consumes a fraction of the time needed by the proportional rate constraints scheme. Copyright © 2011 John Wiley & Sons, Ltd.

Modeling radio resource management in cognitive radio system based on OFDMA using colored Petri Net

Cognitive Radio (CR) system based on Orthogonal Frequency Division Multiple Access (OFDMA), such as Wireless Regional Area Networks (WRAN) and Worldwide Interoperability for Microwave Access (WiMAX), often attempt to improve performance via dynamic radio resource management, which is characterized as concurrent processing of different traffic and nondeterministic system capacity. It is essential to design and evaluate such complex system using proper modeling and analysis tools. In the previous work, most of the communication systems were modeled as Markov Chain (MC) and Stochastic Petri Nets (SPN), which have the explicit limitation in evaluating adaptive OFDMA CR system with wide area traffic. In this paper, we develop an executable top-down hierarchical Colored Petri Net (CPN) model for adaptive OFDMA CR system, and analyze its performance using CPN tools. The results demonstrate that the CPN can model different radio resource management algorithms in CR Systems, and the CPN tools require less computational effort than Markov model using Matlab, with its flexibility and adaptability to the traffics which arrival interval and processing time are not exponentially distributed.

Interference-Based Dynamic Pricing for WCDMA Networks Using Neurodynamic Programming

We study the problem of optimal integrated dynamic pricing and radio resource management, in terms of resource allocation and call admission control, in a WCDMA network. In such interference-limited network, one's resource usage also degrades the utility of others. A new parameter noise rise factor, which indicates the amount of interference generated by a call, is suggested as a basis for setting price to make users accountable for the congestion externality of their usage. The methods of dynamic programming (DP) are unsuitable for problems with large state spaces due to the associated ldquocurse of dimensionality.rdquo To overcome this, we solve the problem using a simulation-based neurodynamic programming (NDP) method with an action-dependent approximation architecture. Our results show that the proposed optimal policy provides significant average reward and congestion improvement over conventional policies that charge users based on their load factor.

A dynamic radio resource management technique for multiple APs in WLANs

As more and more wireless LANs are deployed in many popular locations, there is a need for dynamic radio resource management (RRM) schemes. This paper proposes a new dynamic RRM technique for multiple APs network. First, we develop a real-time algorithm to estimate the number of active stations from the standpoint of an AP, instead of a station. Second, we propose a dynamic RRM algorithm that not only significantly increases network performance but also reduces the co-channel interference. Third, we find the optimal switching probability that minimizes the transient time for an AP to reach its equilibrium state. For uniform traffic conditions, our scheme produces classical optimal frequency assignments. For non-uniform traffic conditions, it produces sub-optimal frequency assignments. Our simulations have shown that the proposed RRM technique adapts to dynamic network conditions and increases the channel throughput up to 65% in less than 20 iterations. The results can be applied to practical WLANs to significantly improve network performance

Dynamic single frequency networks

Wireless asymmetric Internet access with a downlink peak bit rate of 10 to 30 Mb/s can be achieved by using the terrestrial digital video broadcasting system (DVB-T) as a supplemental downlink together with today's cellular systems. This paper is a study of dynamic radio resource management on a packet-by-packet basis for this broadband downlink. The dynamic single frequency networks (DSFN) scheme is evaluated. It exploits the macrodiversity capability of the OFDM modulation scheme. The transmitters are dynamically divided into groups of transmitters that send the same information at the same channel frequency simultaneously. The fairly shared spectrum efficiency (FSSE), in bits per second per Hertz per site, which is a combined measurement of maximum throughput and fairness, is evaluated for best-effort traffic. DSFN improves the FSSE by 100% to 370%, for a certain set of test cases, in comparison to the dynamic packet assignment (DPA) scheme, which combines packet scheduling with dynamic channel assignment (DCA).