Deep and robust resource allocation for random access network based with imperfect CSI

A deep and robust resource allocation framework was proposed for the random access based wireless networks,where both the communication channel state information (C-CSI) and the interference channel state information (I-CSI) were uncertain.The proposed resource allocation framework considered the optimization objective of wireless networks as a learning problem and employs deep neural network (DNN) to approximate optimal resource allocation policy through unsupervised manner.By modeling the uncertainties of CSI as ellipsoid sets,two concatenated DNN units were proposed,where the first was uncertain CSI processing unit and the second was the power control unit.Then,an alternating iterative training algorithm was developed to jointly train the two concatenated DNN units.Finally,the simulations verify the effectiveness of the proposed robust leaning approach over the nonrobust one.     

Utility‐based resource allocation in uplink of OFDMA‐based cognitive radio networks

Cognitive radio makes it possible for an unlicensed user to access a spectrum opportunistically on the basis of non‐interfering to licensed users. This paper addresses the problem of resource allocation for multiaccess channel (MAC) of OFDMA‐based cognitive radio networks. The objective is to maximize the system utility, which is used as an approach to balance the efficiency and fairness of wireless resource allocation. First, a theoretical framework is provided, where necessary and sufficient conditions for utility‐based optimal subcarrier assignment and power allocation are presented under certain constraints. Second, based on the theoretical framework, effective algorithms are devised for more practical conditions, including ellipsoid method for Lagrangian multipliers iteration and Frank–Wolfe method for marginal utilities iteration. Third, it is shown that the proposed scheme does not have to track the instantaneous channel state via an outage‐probability‐based solution. In the end, numerical results have confirmed that the utility‐based resource allocation can achieve the optimal system performance and guarantee fairness. Copyright © 2009 John Wiley & Sons, Ltd.     

Priority‐based adaptive access barring for M2M communications in LTE networks using learning automata

Supporting a huge number of machine‐to‐machine devices with different priorities in Long Term Evolution networks is addressed in this paper. We propose a learning automaton (LA)–based scheme for dynamically allocating random access resources to different classes of machine‐to‐machine devices according to their priorities and their demands in each cycle. We then use another LA‐based scheme to adjust the barring factor for each class to control the possible overload. We show that by appropriate updating procedure for these LAs, the system performance asymptotically converges to the optimal performance in which the evolved node B knows the number of access‐attempting devices from each class a priori. Simulation results are provided to show the performance of the proposed scheme in random access resource allocation to defined classes and adjusting the barring factor for each of them.     

Utility‐optimal cross‐layer resource allocation in distributed wireless cooperative networks

In this paper, we propose a distributed cross‐layer resource allocation algorithm for wireless cooperative networks based on a network utility maximization framework. The algorithm provides solutions to relay selections, flow pass probabilities, transmit rate, and power levels jointly with optimal congestion control and power control through balancing link and physical layers such that the network‐wide utility is optimized. Via dual decomposition and subgradient method, we solve the utility‐optimal resource allocation problem by subproblems in different layers of the protocol stack. Furthermore, by introducing a concept of pseudochannel gain, we model both the primal direct logical link and its corresponding cooperative transmission link as a single virtual direct logical link to simplify our network utility framework. Eventually, the algorithm determines its primal resource allocation levels by employing reverse‐engineering of the pseudochannel gain model. Numerical experiments show that the convergence of the proposed algorithm can be obtained and the performance of the optimized network can be improved significantly. Copyright © 2012 John Wiley & Sons, Ltd.     

Network coding‐based channel quality indicator reporting for two‐way multi‐relay networks

This paper considers channel quality indicator (CQI) reporting for data exchange in a two‐way multi‐relay network. We first propose an efficient CQI reporting scheme based on network coding, where two terminals are allowed to simultaneously estimate the CQI of the distant terminal‐relay link without suffering from additional overhead. In addition, the transmission time for CQI feedback at the relays is reduced by half while the increase in complexity and the loss of performance are negligible. This results in a system throughput improvement of 16.7% with our proposed CQI reporting. Upper and lower bounds of the mean square error (MSE) of the estimated CQI are derived to study performance behaviour of our proposed scheme. It is found that the MSE of the estimated CQI increases proportionally with the square of the cardinality of CQI level sets although an increased number of CQI levels would eventually lead to a higher data rate transmission. On the basis of the derived bounds, a low‐complexity relay selection (RS) scheme is then proposed. Simulation results show that, in comparison with optimal methods, our suboptimal bound‐based RS scheme achieves satisfactory performance while reducing the complexity at least three times in case of large number of relays. Copyright © 2012 John Wiley & Sons, Ltd.     

Distributed cross‐layer optimization for wireless regional area network‐based cognitive radio networks

This paper presents a study of a cross‐layer design through joint optimization of spectrum allocation and power control for cognitive radio networks (CRNs). The spectrum of interest is divided into independent channels licensed to a set of primary users (PUs). The secondary users are activated only if the transmissions do not cause excessive interference to PUs. In particular, this paper studies the downlink channel assignment and power control in a CRN with the coexistence of PUs and secondary users. The objective was to maximize the total throughput of a CRN. A mathematical model is presented and subsequently formulated as a binary integer programming problem, which belongs to the class of non‐deterministic polynomial‐time hard problems. Subsequently, we develop a distributed algorithm to obtain sub‐optimal results with lower computational complexity. The distributed algorithm iteratively improves the network throughput, which consists of several modules including maximum power calculation, excluded channel sets recording, base station throughput estimation, base station sorting, and channel usage implementation. Through investigating the impacts of the different parameters, simulation results demonstrates that the distributed algorithm can achieve a better performance than two other schemes. Copyright © 2011 John Wiley & Sons, Ltd.     

Opportunistic delay‐margin‐based resource allocation for next‐generation wireless networks

This paper studies and develops efficient traffic management techniques for downlink transmission at the base station (BS) of multi‐service IP‐based networks by combining quality‐of‐service (QoS) provision and opportunistic wireless resource allocation. A delay‐margin‐based scheduling (DMS) for downlink traffic flows based on the delays that each packet has experienced up to the BS is proposed. The instantaneous delay margin, represented by the difference between the required and instantaneous delays, quantifies how urgent the packet is, and thus it can determine the queuing priority that should be given to the packet. The proposed DMS is further integrated with the opportunistic scheduling (OPS) to develop various queueing architectures to increase the wireless channel bandwidth efficiency. Different proposed integration approaches are investigated and compared in terms of delay outage probability and wireless channel bandwidth efficiency by simulation. Copyright © 2010 John Wiley & Sons, Ltd.     

Fair coding for inter‐session network coding in wireless mesh networks

Because of the broadcast and overhearing capability of wireless networks, network coding can greatly improve throughput in wireless networks. However, our investigation of existing inter‐session network coding protocols found that the short‐term unfairness that existed in 802.11‐based medium access control (MAC) protocols actually decreases the coding opportunity, which in turn compromises the throughput gain of network coding. To alleviate the negative impact of this unfairness, we propose a coding‐aware cross‐layer heuristic approach to optimize the coordination of network coding and MAC layer protocol, named FairCoding, which can significantly increase coding opportunities for inter‐session network coding through a fair short‐term traffic allocation for different coding flows. Experiment evaluation shows that the proposed mechanism can bring more coding opportunities and improve the total throughput of wireless mesh networks by up to 20%, compared with the coding mechanism, without considering the negative impact of the short‐term unfairness. Copyright © 2015 John Wiley & Sons, Ltd.     

Link optimization for energy‐constrained wireless networks with packet retransmissions

With the objective to minimize the energy consumption for packet based communications in energy‐constrained wireless networks, this paper establishes a theoretical model for the joint optimization of the parameters at the physical layer and data link layer. Multilevel quadrature amplitude modulation (MQAM) and automatic repeat request (ARQ) techniques are considered in the system model. The optimization problem is formulated into a three dimensional nonlinear integer programming (NIP) problem with the modulation order, packet size, and retransmission limit as variables. For the retransmission limit, a simple search method is applied to degenerate the three dimensional problem into a two dimensional NIP problem, for which two optimization algorithms are proposed. One is the successive quadratic programming (SQP) algorithm, combining with the continuous relaxation based branch‐and‐bound method, which can obtain the global optimal solution since the continuous relaxation problem is proved to be hidden convex. The other is a low‐complexity sub‐optimal iterative algorithm, combining with the nearest‐neighboring method, which can be implemented with a polynomial complexity. Numerical examples are given to illustrate the optimization solution, which suggests that the joint optimization of the physical/data link layer parameters contributes noticeably to the energy saving in energy‐constrained wireless networks. Copyright © 2010 John Wiley & Sons, Ltd.     

Throughput reliability analysis of cloud‐radio access networks

This paper develops a stochastic geometry‐based analytical approach for calculating the throughput reliability of a cloud‐radio access network (C‐RAN) comprising randomly distributed remote radio heads (RRHs) and randomly located users. A tunable distance‐based RRH transmit power control mechanism along with cooperative joint transmissions by the RRHs is employed to achieve power savings and high throughput reliability. The analytical result for the throughput reliability serves as input to analysis of per user achievable average rate and C‐RAN network‐level performance metrics of spectral efficiency and energy efficiency. The analytical results are validated by Monte Carlo simulation results with good agreement, thus confirming the accuracy of the developed analytical approach. The key finding from the analysis is that by carefully tuning the RRH transmit power and cooperation parameter (cluster radius), it is possible to realize a threefold improvement in the energy efficiency along with 108% enhancement in the spectral efficiency of C‐RANs. Copyright © 2016 John Wiley & Sons, Ltd.     

Random network coding‐based optimal scheme for perfect wireless packet retransmission problems

Solving wireless packet retransmission problems (WPRTPs) using network coding (NC) approach is increasingly attracting research efforts. However, existing researches are almost all focused on solutions in Galois field GF(2), and consequently, the solutions found by these schemes are usually less optimal. In this paper, we focus on optimal NC‐based scheme for perfect WPRTPs (P‐WPRTPs) where, with respect to each receiver, a packet is either requested by or already known to it. The number of retransmitted packets in optimal NC‐based solutions to P‐WPRTPs is firstly analyzed and proved. Then, random network coding‐based optimal scheme (RNCOPT) is proposed for P‐WRPTPs. RNCOPT is optimal in the sense that it guarantees to obtain a valid solution with minimum number of packet retransmissions. Furthermore, in RNCOPT, each coding vector is generated using a publicly known pseudorandom function with a randomly selected seed. The seed, instead of the coding vector, is used as decoding information to be retransmitted together with the coded packet. Thus, packet overhead of RNCOPT is reduced further. Extensive simulations show that RNCOPT distinctively outperforms some previous typical schemes for P‐WPRTPs in saving the number of retransmitted packets. Copyright © 2011 John Wiley & Sons, Ltd.     

Joint collision resolution and transmit‐power adjustment for Aloha‐type random access

We consider uplink random access for which slotted Aloha has usually been employed with unknown channel conditions. Upon failure of a transmission attempt, a user cannot tell whether the failure was caused by collision with other simultaneously transmitting users or by his use of insufficient transmit power. If a transmission attempt failed due to collision which could have been resolved by retransmission, increasing transmit power would just waste power and, moreover, reduce the other users' chance of successful access. To handle this lack of information on the cause of failure, we propose a novel Cause‐of‐Failure resolution, where the transmit power is increased after a given number of consecutive unsuccessful access attempts when the probability that a given failure is caused by collision becomes sufficiently low. To exploit the thus‐obtained transmit power for the next random access attempt, we also determine the Cause‐of‐Success based on the number of consecutive successful attempts, i.e., whether to (probabilistically) decrease or maintain the current transmit power. This way, users can adjust their transmit power for random access, which we call Auto Power Fallback (APF), considered as an advanced version of the power ramping algorithm. We evaluate APF by modeling analysis and numerical computation based on the slotted Aloha, showing that APF determines a suitable transmit power for uplink random accesses while achieving good performance. Copyright © 2011 John Wiley & Sons, Ltd.     

QoE‐ and energy‐efficient resource optimization in OFDMA networks with bidirectional relaying

Because of the surging demands of multimedia services, quality‐of‐experience (QoE) is becoming an important metric to evaluate network quality from users' perspective. In this paper, resource optimisation to achieve optimal tradeoff between QoE and energy consumption in bidirectional orthogonal frequency‐division multiple‐access relaying networks is addressed so as to provide satisfactory multimedia delivery quality and support green communications. We first formulate a QoE‐energy efficiency tradeoff optimisation where QoE requirements and relaying traffic balance are considered and prove that QoE‐energy efficiency is quasiconcave on QoE, which suggests the existence of a unique global optimal tradeoff point. We then propose an optimisation framework to achieve the optimal tradeoff efficiently. With the framework, we develop resource allocation approaches for two specific relaying strategies, that is, two‐phase decode‐and‐forward relaying with dynamic XOR network coding and compute‐and‐forward relaying with physical network coding via structured codes. Numerical results validate theoretical findings and demonstrate the effectiveness of the proposed optimisation solution for achieving the tradeoff between QoE and energy consumption. Copyright © 2015 John Wiley & Sons, Ltd.     

A joint resource allocation‐channel coding design based on distributed source coding

Wireless sensor networks (WSNs) have found a wide variety of applications recently. However, the challenges in WSNs still remain in improving the sensor energy efficiency and information quality (distortion reduction) of the sensing data transmissions. In this paper, we propose a novel cross‐layer design of resource allocation and channel coding to protect distributed source coding (DSC)‐based data transmission. Resource allocation strategies include rate adaptation and automatic repeat‐request retransmissions. Our proposed joint design of resource allocation, channel coding, and DSC can improve the network energy efficiency and information quality while meeting the data transmission latency requirements. Further, we investigate how the resource allocation enables the network to achieve unequal error protection among correlated DSC streams. Our simulation studies demonstrate that the proposed joint design significantly improves the DSC‐based data transmission quality and the network energy efficiency. Copyright © 2013 John Wiley & Sons, Ltd.     

A distributed utility‐based scheduling for peer‐to‐peer video streaming over wireless networks

Interactive multimedia applications such as peer‐to‐peer (P2P) video services over the Internet have gained increasing popularity during the past few years. However, the adopted Internet‐based P2P overlay network architecture hides the underlying network topology, assuming that channel quality is always in perfect condition. Because of the time‐varying nature of wireless channels, this hardly meets the user‐perceived video quality requirement when used in wireless environments. Considering the tightly coupled relationship between P2P overlay networks and the underlying networks, we propose a distributed utility‐based scheduling algorithm on the basis of a quality‐driven cross‐layer design framework to jointly optimize the parameters of different network layers to achieve highly improved video quality for P2P video streaming services in wireless networks. In this paper, the quality‐driven P2P scheduling algorithm is formulated into a distributed utility‐based distortion‐delay optimization problem, where the expected video distortion is minimized under the constraint of a given packet playback deadline to select the optimal combination of system parameters residing in different network layers. Specifically, encoding behaviors, network congestion, Automatic Repeat Request/Query (ARQ), and modulation and coding are jointly considered. Then, we provide the algorithmic solution to the formulated problem. The distributed optimization running on each peer node adopted in the proposed scheduling algorithm greatly reduces the computational intensity. Extensive experimental results also demonstrate 4–14 dB quality enhancement in terms of peak signal‐to‐noise ratio by using the proposed scheduling algorithm. Copyright © 2015 John Wiley & Sons, Ltd.     

Energy consumption optimization for self‐powered IoT networks with non‐orthogonal multiple access

Energy harvesting (EH) has been considered as one of the promising technologies to power Internet of Things (IoT) devices in self‐powered IoT networks. By adopting a typical harvest‐then‐transmit mode, IoT devices with the EH technology first harvest energy by using wireless power transfer (WPT) and then carry out wireless information transmission (WIT), which leads to the coordination between WPT and WIT. In this paper, we consider optimizing energy consumption of periodical data collection in a self‐powered IoT network with non‐orthogonal multiple access (NOMA). Particularly, we take into account time allocation for the WPT and WIT stages, node deployment, and constraints for data transmission. Moreover, to thoroughly explore the impact of different multiple access methods, we theoretically analyse and compare the performance achieved by employing NOMA, frequency division multiple access (FDMA), and time division multiple access (TDMA) in the considered IoT network. To validate the performance of the proposed method, we conduct extensive simulations and show that the NOMA outperforms the FDMA and TDMA in terms of energy consumption and transmission power.     

Design of reliable fiber‐based distribution networks modeled by multi‐objective combinatorial optimization

In this work, we investigate the planning of hybrid fiber/very high bit rate digital subscriber line (HFV) access networks. This HFV variant is considered as an alternative to passive optical access network. It consists of implementing optical fibers in the access network part from the central office to the street cabinets, whereas the very high bit rate digital subscriber line technology is used in the last meter part, from street cabinets to subscribers. Firstly, we discuss the different tasks of this planning problem. We model this planning problem as a multi‐objective optimization problem, where different conflicting objectives have to be optimized at the same time. We consider network costs and network reliability. This problem is solved by two different approaches: the classical single‐objective optimization (SOO) and the multi‐objective optimization (MOO), which is a recent optimization approach that is gaining an increasing interest in practical optimization problems. MOO solves the problem by searching for different optimal trade‐offs between the optimization objectives. The performances of SOO and MOO are analyzed and compared with each other using three network instances. Copyright © 2012 John Wiley & Sons, Ltd.     

MIMO系统下随机接入的实现及吞吐量研究

随机接入技术作为LTE系统中的关键技术之一,接入成功率关系到传输时延,LTE系统下的随机接入所采用的传统冲突解决算法主要是基于网络层的重传机制。提出了一种MIMO下的随机接入实现方案,基站端可以利用多天线接收和先进的MIMO信号处理技术的结合,进而联合高层解决冲突,仿真结果表明了该方案可以显著地提高系统的吞吐量。     

A load‐balancing and coding‐aware multicast protocol for mobile ad hoc networks

In this paper, we propose a Load‐Balancing and Coding‐Aware Multicast (LCM) protocol for mobile ad hoc networks. In LCM protocol, a new route metric named Expected Transmission Time with Coding and Load Balancing (ETTCL) is presented at first, aiming at effectively selecting the path not only that has the possible coding opportunity but also where overflow due to network overload can be prevented. Then, we describe the route discovery phase by constructing the node‐disjoint multicast tree on the basis of ETTCL and employ network coding to encode the data flows for route maintenance. The effectiveness of LCM protocol is simulated and analyzed by NS‐2, which shows that this protocol has good performance in reducing average end‐to‐end delay and control overhead and can improve packet delivery ratio compared with the existing protocol. Copyright © 2015 John Wiley & Sons, Ltd.     

A capture‐assisted random access scheme for multi‐beam LEO satellite packet data networks

A CDMA‐based satellite switch is proposed for use in multi‐beam satellites carrying random‐access packet‐switched data. Applications include the emerging new low‐earth‐orbit (LEO) satellite networks which support global wireless networking. Capture phenomenon is used to advantage in increasing the random access throughput, and the on‐board switch is at once simple and specially designed to handle full loads with minimal complexity. Copyright © 2004 John Wiley & Sons, Ltd.