Cross-layer Algorithm Research Articles

Cross Layer Relay Selection in Device-to-Device Communication

Cross layer optimization for relay assisted wireless communication is important as it caters for parameters in more than one layer thereby a more holistic insight to the performance of proposed algorithms is realised. Due to the nature of the wireless channel, the availability of perfect channel state information may not be guaranteed. Moreover for relay selection algorithms, where mobile user equipment are used as relays, optimizing a relay defined utility can motivate relaying. This work proposes a cross layer stable matching based relay selection algorithm for relay assisted device-to-device communication. The cross layer parameter defined by this work is a function of data rate at the physical layer and queueing state information at the media access control sub-layer. The selection problem is modelled as an optimization problem for which stable matching is used to suitably allocate relay-enabled user equipment to source-destination pairs. To evaluate the performance of the proposed algorithm, spectral efficiency, energy efficiency and fairness were used as performance metrics. The proposed cross layer algorithm was compared with the best source-relay selection algorithm, best relay-destination selection algorithm and a random selection algorithm. Unlike other works, our proposed algorithm is channel uncertainty aware. The proposed cross layer selection algorithm was shown through simulations to offer improved spectral efficiency performance of 16% over the random selection algorithm. Furthermore, there was a fairness improvement of 0.01 and 0.02 over the best source—relay and the best relay—destination selection algorithms respectively.

Cross-layer optimization technology for wireless network multimedia video

With the development of communication technology, wireless Internet has become more and more popular. The traditional network layered protocols cannot meet the increasingly rich network services, especially video. This paper briefly introduced the cross-layer transmission of video in wireless network and the cross-layer optimization algorithm used for improving video transmission quality and improved the traditional cross-layer algorithm. Then, the two cross-layer algorithms were simulated and analyzed on MATLAB software. The results showed that the packet delivery rate, peak signal to noise ratio and downlink throughput of the improved cross-layer algorithm were significantly higher than those of the traditional cross-layer algorithm under the same signal to interference plus noise ratio of receiving users in wireless network; meanwhile, with the increase of signal to interference plus noise ratio of the receiving user, the packet delivery rate and peak signal to noise ratio of the two algorithms increased, and tended to be stable after some signal to interference plus noise ratio, while the throughput of the two algorithms increased linearly. In the established real wireless network, the package delivery rate, peak signal to noise ratio and throughput of video after application of cross-layer algorithm were significantly improved, and the wireless network applying the improved cross-layer algorithm improved more. In summary, compared with the traditional cross-layer algorithm, the improved cross-layer algorithm can better improve the transmission quality of video in wireless network.

MRCSC: A cross-layer algorithm for joint Multicast Routing, Channel selection, Scheduling, and Call admission control in multi-cell multi-channel multi-radio cognitive radio wireless networks

This paper addresses the problem of joint multicast routing, channel selection, scheduling, and call admission control in multi-cell multi-channel multi-radio cognitive radio wireless mesh networks. The applied model relies on the QoS sessions, where each one is expressed with a bandwidth requirement. We propose a cross-layer algorithm named “Multicast Routing, Channel selection, Scheduling, and Call admission control (MRCSC)”. The proposed scheme, considering wireless broadcast advantage, channel/radio diversity, and spatial reuse, uses both intra- and inter-cell relaying to create multicast trees with a specific bandwidth. MRCSC considers both inter-flow and intra-flow interferences. It adopts an efficient collision-free mechanism to greedily schedule different multicast transmission in the network. As an advantage, considering the multi-radio technology, MRCSC allows the nodes to simultaneously send/receive data on different available non-overlapping channels. Numerical results of our comprehensive simulations confirm the efficiency of the MRCSC algorithm in terms of the number of transmissions, stability, and multicast period.

Throughput Analysis on MIMO-OFDM with Modified QoS Guarantee Cross Layer Algorithm

Throughput Analysis on MIMO-OFDM with Modified QoS Guarantee Cross Layer Algorithm

EMSC: a joint multicast routing, scheduling, and call admission control in multi-radio multi-channel WMNs

This paper deals with the problem of joint multicast routing, scheduling, and call admission control in multiradio multi-channel wireless mesh networks. To heuristically solve this problem, we propose a cross-layer algorithm named “extended MIMCR with scheduling and call admission control phases (EMSC)”. Our model relies on the on-demand quality of service (QoS) multicast sessions, where each admitted session creates a unique tree with a required bandwidth. The proposed scheme extends the MIMCR algorithm to fairly schedule multiple non-interfering transmissions in the same time slot. It also exploits a call admission control mechanism to protect the QoS requirements of the multicast traffics. EMSC reduces the number of occupied time slots, with consideration of spatial reuse, both Intra-flow and Inter-flow interferences, and selecting the minimum-interference minimum-cost paths. This subsequently leads to better radio resource utilization and increases the network throughput. Simulation results show that the proposed algorithm outperforms the other algorithms and improves the network performance.

QoS Strategies for Wireless Multimedia Sensor Networks in the Context of IoT at the MAC Layer, Application Layer, and Cross-Layer Algorithms

Wireless multimedia sensor networks (WMSNs) have got capacity to collect both scalar sensor data and multidimensional sensor data. It is the basis for the Internet of things (IoT). Quality of service (QoS) pointers like energy efficiency, reliability, bit error rate, and latency can be helpful in data collection estimation over a network. In this paper, we review a number of QoS strategies for WMSNs and wireless sensor networks (WSNs) in the IoT context from the perspective of the MAC and application layers as well as the cross-layer paradigm. Considering the MAC layer, since it is responsible for regulating the admittance to the shared medium and transmission reliability and efficiency through error correction in wireless transmissions, and for performance of framing, addressing, and flow control, the MAC protocol design greatly affects energy efficiency. We thus review a number of protocols here including contention-free and contention-based protocols as well as the hybrid of these. This paper also surveys a number of state-of-the-art machine-to-machine, publish/subscribe, and request/response protocols at the application layer. Cross-layer QoS strategies are very vital when it comes to system optimization. Many cross-layer strategies have been reviewed. For these QoS strategies, the challenges and opportunities are reviewed at each of the layers considered. Lastly, the future research directions for QoS strategies are discussed for research and application before concluding this paper.

Design of Multichannel and Multihop Low-Power Wide-Area Network for Aircraft Vibration Monitoring

Vibration-based condition monitoring among all the components of the aircraft structure is an important approach to improve the flight safety before any component in aircraft reaches resonance. This paper presents multichannel and multihop low-power wide-area network (MCMHL) architecture suitable for vibration monitoring on aircraft. First, microelectro mechanical system-long Range (LoRa)-based sensor node architecture in light of hardware cross-layer algorithm is proposed for implementing the tradeoff among hardware cost, power consumption, and performance. To achieve high accuracy of synchronous acquisition, multihop slot segmenting scheduling and multichannel data communication algorithm are proposed. In addition, the beacon transmission delay, of beacon between sink and sensor nodes is calculated, and further synchronization compensation algorithm is designed. The experiments of the proposed approach in aircraft vibration test and data synchronization test on aircraft skin are validated, showing that the proposed MCMHL approach has these abilities of data synchronous collections, remote communication, and data stream uploading in a wide monitoring area.

Design and Experimental Evaluation of a Cross-Layer Deadline-Based Joint Routing and Spectrum Allocation Algorithm

The design and implementation of a novel distributed deadline-based routing and spectrum allocation algorithm for tactical ad-hoc networks is reported in this article. Different traffic classes including text, voice, surveillance video, and threat alert among others need to be handled by these networks. Each of these traffic classes have different quality of service (QoS) based deadline requirements. Additionally, these networks are characterized by dynamic channel and traffic conditions that vary with time and location. Even under these conditions, it is critical to receive packets before the deadline expires to make rapid decisions in the battlefield. Therefore, a tactical ad-hoc network should be able to adapt to these requirements and maximize the number of packets delivered to the destination within the specified deadline. A distributed deadline-based routing and spectrum allocation algorithm is designed to maximize the utilization of the available resources and ensure delivery of packets within the deadline constraints. To this end, a weighted virtual queue (VQ) that is used to construct the network utility function is defined. Accordingly, the optimal session, next hop, transmit power, and frequency is determined by the distributed algorithm to ensure efficient utilization of the available resources. Hence, maximizing the delivery of packets to the intended destination within the specified deadline. The 49 node simulation shows up to 35 percent improvement in effective throughput and 26 percent improvement in reliability as compared to joint ROuting and Spectrum Allocation algorithm (ROSA), which does not adapt according to the deadline requirements of the data flowing through the network. As a secondary objective, this work advances the state of the art of the experimental cross-layer framework to address the challenges involved in having such cross-layer algorithms implemented on a testbed. The required flexibility to change the transmission parameters on-the-fly is provided by the proposed framework. The network is designed to enable the data exchange between neighbors using custom designed control packets (which might be different for different algorithms) since this information is critical for nodes to perform optimization. Cross-layer optimization is achieved by means of data management and control entities that enable information exchange between layers. The practicality of the proposed solution was proven by having the novel algorithm implemented on a five-node software defined radio testbed which leverages the proposed cross-layer framework. In contrast to ROSA, the proposed algorithm demonstrated up to 17 percent improvement in terms of throughput and reliability. The performance improvement achieved is expected to increase on a larger network deployment.

Dynamic Spectrum Access for Multimedia Transmission Over Multi-User, Multi-Channel Cognitive Radio Networks

The optimal spectrum access strategy is investigated for multi-user multi-channel scenario in cognitive radio networks. At first, an online learning method based on Dirichlet Process is adopted to predict the channel usage based on ACK/NACK feedbacks, which can avoid frequent information exchange among users. Based on the prediction result, the delay performance can be computed when a user transmits certain percentage of multimedia packets on a specific channel. Second, the packet delivery ratio (PDR) is derived from the prediction result of channel usage to reflect the accessing competition among multiple users. Finally, the quality of service (QoS) of multimedia applications is defined as the joint delay and throughput performances. Moreover, a dynamic spectrum access scheme is proposed to optimize the QoS metrics. The simulation results demonstrate that the QoS and the peak-signal-to-noise ratio (PSNR) of the proposed spectrum access algorithm outperform the three existing spectrum access algorithms, i.e., cognitive cross-layer algorithm, dynamic learning algorithm, and dynamic least interference algorithm. The proposed algorithm achieves more than 21.8%, 5.4%, and 3.9% PDR enhancement and over 3.23 dB, 0.82 dB, and 0.50 dB PSNR gains, compared with those three algorithms, given the transmission power as 10, 20, and 30 units, respectively.

Joint rate adaptation and resource allocation for real-time H.265/HEVC video transmission over uplink OFDMA systems

We consider multiuser video communication over uplink orthogonal frequency-division multiple access (OFDMA) systems. A cross-layer algorithm of joint bit allocation, packet scheduling and wireless resource assignment are proposed to minimize the end-to-end expected video distortion. Video rate adaptation is performed under the wireless resource constraints. The target number of encoding bits for each video packet is obtained to minimize the estimated distortion based on the online content-based rate-distortion function. Due to the inaccuracy of the rate control algorithm in H.265/HEVC encoding, the actual number of bits may differ from the target. Accordingly, the actual encoder distortion may deviate from the estimated distortion. Then, we propose an iterative algorithm to re-assign wireless resources based on the actual number of encoded bits to obtain the final resource allocation policy and packet scheduling decision. Numerical simulation results show that our proposed approach significantly outperforms the baseline algorithms in terms of received video quality.

Effective 5G Wireless Downlink Scheduling and Resource Allocation in Cyber-Physical Systems

In emerging Cyber-Physical Systems (CPS), the demand for higher communication performance and enhanced wireless connectivity is increasing fast. To address the issue, in our recent work, we proposed a dynamic programming algorithm with polynomial time complexity for effective cross-layer downlink Scheduling and Resource Allocation (SRA) considering the channel and queue state, while supporting fairness. In this paper, we extend the SRA algorithm to consider 5G use-cases, namely enhanced Machine Type Communication (eMTC), Ultra-Reliable Low Latency Communication (URLLC) and enhanced Mobile BroadBand (eMBB). In a simulation study, we evaluate the performance of our SRA algorithm in comparison to an advanced greedy cross-layer algorithm for eMTC, URLLC and LTE (long-term evolution). For eMTC and URLLC, our SRA method outperforms the greedy approach by up to 17.24%, 18.1%, 2.5% and 1.5% in terms of average goodput, correlation impact, goodput fairness and delay fairness, respectively. In the case of LTE, our approach outperforms the greedy method by 60%, 2.6% and 1.6% in terms of goodput, goodput fairness and delay fairness compared with tested baseline.

Joint Dynamic Rate Control and Transmission Scheduling for Scalable Video Multirate Multicast Over Wireless Networks

In this paper we consider the time-varying characteristics of practical wireless networks and propose a joint dynamic rate allocation and transmission scheduling optimization scheme for scalable video multirate multicast based on opportunistic routing (OR) and network coding. With OR the decision of optimal routes for scalable video coding layered streaming is integrated into the joint optimization formulation. The network throughput is also increased by taking advantage of the broadcast nature of the wireless shared medium and by network coding operations in intermediate nodes. To maximize the overall video reception quality among all destinations the proposed scheme can jointly optimize the video reception rate the associated routes to different destinations and the time fraction scheduling of transmitter sets that are concurrently transmitting in the shared wireless medium. By using dual decomposition and primal-dual update approach we develop a cross-layer algorithm in a fully distributed manner. Simulation results demonstrate significant network multicast throughput improvement and adaptation to dynamic network changes relative to existing optimization schemes.

Cross-layer control of wireless sensor network for smart distribution grid

This paper presents an integrated modelling method to provide cross-layer control algorithm for wireless sensor network (WSN) suited to smart distribution grid communication. The proposed algorithm is designed for improving the quality of service (QoS) of WSN communication. The cross-layer control algorithm is established, by sharing information from different protocol layers. The state parameters of different protocol layers are transformed into the corresponding concept nodes of the fuzzy cognitive map (FCM). Influence coefficients representing the subordinate relationships of different protocol layers are obtained according to state information in the previous moment. The control program is automatically set and completed by embedding FCM into WSN communication system. The proposed algorithm has been experimentally implemented and evaluated on a tested WSN with 1 coordinator node and 10 terminal/routing nodes. Experimental results show that the proposed control scheme ensures the requirements of real-time and reliability for smart distribution grid communication.

Load-aware multicast routing in multi-radio wireless mesh networks using FCA-CMAC neural network

Multicasting is a useful network service in wireless mesh networks (WMNs) for delivering same data from a source to multiple destinations. An effective multicast routing protocol in multi-channel multi-radio WMNs (MCMR-WMNs) is required to satisfy the following criteria together: high network throughput, low end-to-end delay, low tree cost, low computational time, and load-aware routing. Furthermore, how to fully exploit channel diversity in MCMR-WMNs to accomplish low channel interference criteria is a critical issue in designing multicast routing protocol. In spite of its significance, multicast routing which satisfies all of the mentioned criteria, has not drawn much attention so far. Besides, major multicast routing protocols proposed in MCMR-WMNs are centralized or solve two problems of multicast tree construction and channel assignment sequentially. These protocols are time-consuming in addition to suffering from a single-point-of-failure. In this paper, we propose a distributed cross-layer algorithm for joint multicast routing and channel assignment in MCMR-WMNs. For the first time, we apply fuzzy credit assigned cerebellum model articulation controller (FCA-CMAC) neural network model to construct multicast routing tree considering load on the mesh nodes and the delay between neighboring mesh nodes. Moreover, we present a heuristic channel assignment algorithm aiming to reduce interference among the links of the multicast tree. FCA-CMAC converges quickly and creates minimal delay and load-aware multicast tree. Therefore, proposed method can optimize the network throughput, end-to-end delay, tree cost, and computational time. Additionally, channel assignment algorithm is subject to produce the minimal interference multicast tree. Simulation results show that in terms of aforementioned criteria, the proposed FCA-CMAC based multicast algorithm achieves better performance than those comparative references.

Subcarrier Assignment and Power Allocation for Device-to-Device Video Transmission in Rayleigh Fading Channels

Subcarrier assignment and power allocation for device-to-device (D2D) video transmission using a filter bank multicarrier waveform in a Rayleigh fading environment are investigated. We analyze the co-channel interference between D2D pairs, and propose a cross-layer algorithm with a subcarrier assignment outer loop and a power allocation inner loop, which aims to optimize the overall video quality. Unlike the non-convexity in physical layer power allocation for maximizing the total throughput, the cross-layer power allocation problem is convex under certain conditions, so a high quality solution for power allocation can be efficiently found. Simulation results demonstrate a higher overall video quality by the proposed cross-layer algorithm compared with baseline algorithms.

Cross-layer optimization using two-level dual decomposition in multi-flow ad-hoc networks

The conventional protocol architectures based on rigid and inflexible layering principles are not suitable to meet the key challenges posed by ad-hoc networks. To overcome the performance limitations caused by lack of coordination between layers, the communication protocols crossing different layers need to be optimized jointly. In this paper, we explore a novel cross-layer framework for joint optimization of congestion control, routing, contention control, and power control in multi-flow ad-hoc networks. Accordingly, a generalized mathematical model is developed for cross-layer optimization formulation that can seamlessly address these issues with the aid of network utility maximization. Convexity is essential to attain a global optimum solution for the optimization problem in its feasible region. Therefore, the original non-convex optimization problem is convexified through suitable logarithmic transformations. Then, we employ a two-level dual decomposition technique for relaxing the interlayer coupling constraints in the network. In the first level, the problem is vertically decomposed into four disjoint subproblems that are solved independently across transport, network, MAC and physical layers. In the second level, a horizontal decomposition is applied within the physical layer. Each of the four subproblems is jointly correlated through the set of Lagrangian dual variables that control the interlayer coupling. Subsequently, the subgradient projection procedure is used to solve the associated dual problem. For this, a distributed iterative algorithm is proposed to implement the cross-layer approach with static channels and multiple source---destination pairs. Simulation results and analyses depict the global convergence of the convex optimization problem to a unique optimal solution. We also present the convergence process of the dual variables that act as bridges connecting and coordinating the four subproblems. Finally, we compare our proposed cross-layer algorithm with two previous algorithms employing cross-layer deign of two and three layers. Numerical results show that our algorithm offers considerable performance enhancement over the previous work in terms of throughput, persistence probability, and power consumption.

A joint routing and channel assignment in multi-radio multi-channel wireless mesh networks

To reduce inter-link interference and balance networks loads, this paper presents and evaluates a cross-layer algorithm for multi-radio multi-channel wireless mesh networks (WMNs), while conducting routing channel assignments. In channel assignment phase, we propose a greedy algorithm based on a multi-radio multi-channel interference model and select the channel with minimum of interference degree. In the routing phase, a new routing parameter which comprehensively considers interference, delay, load balancing and other factors is proposed. The new algorithm is compared with existing algorithm that is multi-radio multi-channel WMN based on ad hoc on-demand distance vector routing (MRMC-AODV) to illustrate the advantages. When the load reaches 6 Mbps, the throughput exceeds 14% of the MRMC-AODV, with a delay of nearly 80% of the MRMC-AODV latency and it reduces packet loss ratio by about 12%. The simulation results show that this algorithm can effectively improve the network throughput, reduce delay and decrease packet loss ratio.

Low-interference multicast routing in multi-radio multi-channel wireless mesh networks using adaptive directional antennas

This paper deals with the problem of multicast routing in Multi-Radio Multi-Channel Wireless Mesh Networks (MRMC-WMNs) equipped with directional antennas. We jointly consider the wireless broadcast advantage, the directional antenna technology, and the interference-aware path selection metric to improve the network performance. Although using directional antennas reduces the interference, it increases the number of transmissions. The adaptive directional antenna is an effective approach to control this trade-off. In this regard, we propose four cross-layer algorithms named “Directional Transmission aware Multicast Tree (DTMT)”, “Directional Interference-aware Multicast Tree (DIMT)”, “Steerable Beam Multicast routing (SBM)”, and “Interference-aware Steerable Beam Multicast routing (ISBM)”. As an advantage, these algorithms jointly address the problems of multicast tree construction, transmission channel selection, and transmission beam specification. DTMT and DIMT are implemented on three types of graphs called “Random Oriented Graph (ROG)”, “Adaptive Oriented Graph (AOG)”, and “Adaptive beam Graph (ABG)”. AOG and ABG try to find the best sector by steering the directional antennas. Differently, in SBM and ISBM, the beam-width and orientation of each antenna are adaptively characterized during the procedure of the tree construction. Numerical results demonstrate that the proposed algorithms effectively outperform other existing algorithms in terms of the interference and the number of transmissions.

Distributed Scheduling and Delay-Aware Routing in Multihop MR-MC Wireless Networks

In multiradio multichannel (MR-MC) networks with significantly expanded network resource space, many existing scheduling/routing algorithms rely on a link-based network model and apply different heuristics in algorithm design to achieve/approximate throughput optimality. In this paper, using a tuple-based multidimensional conflict graph model, we establish a cross-layer framework, which facilitates systematically studying distributed scheduling and routing in multihop multipath MR-MC networks. In this framework, each tuple link is installed with a routing controller, which feeds controlled amounts of data to the tuple-link output queues for scheduling and transmission. We rigorously prove that, under a set of certain conditions, the network is queue stable in the mean sense under the distributed maximal scheduling policy. Based on Lyapunov optimization, we further propose a distributed delay-aware multipath routing method, which aims at minimizing the end-to-end delay of each commodity flow. Extensive simulation results demonstrate that the proposed joint scheduling/routing algorithm outperforms existing link-based single-path and multipath algorithms and tuple-based cross-layer control algorithm.

Latency optimization through routing-aware time scheduling protocols for wireless sensor networks

Communications in wireless sensor networks are mainly controlled by the temporal decisions of the data link layer and the spatial decisions of the network layer. When taken independently, these decisions may not be correlated which affects the latency metric. To tackle this problem, we propose cross-layer algorithms to define TDMA (Time Division Multiple Access) schedules based on routing information. Two main strategies are applied, based on routing tree traversals or on adapted ones using information from the network’s graph. We also present the Optimal scheduling algorithm which finds the scheduling with the minimal latency; the latter is used to compute the efficiency of our heuristics. Extensive simulations have been performed and show improvement in latency up to 29% compared with existing works. The effect of the heuristics on the duty-cycle is studied in the perspective of energy consumption. The duty-cycle is improved up to 11.54%.