Multi-channel Wireless Research Articles

Machine-Learning Based Channel Quality and Stability Estimation for Stream-Based Multichannel Wireless Sensor Networks.

Wireless sensor networks (WSNs) have become more and more diversified and are today able to also support high data rate applications, such as multimedia. In this case, per-packet channel handshaking/switching may result in inducing additional overheads, such as energy consumption, delays and, therefore, data loss. One of the solutions is to perform stream-based channel allocation where channel handshaking is performed once before transmitting the whole data stream. Deciding stream-based channel allocation is more critical in case of multichannel WSNs where channels of different quality/stability are available and the wish for high performance requires sensor nodes to switch to the best among the available channels. In this work, we will focus on devising mechanisms that perform channel quality/stability estimation in order to improve the accommodation of stream-based communication in multichannel wireless sensor networks. For performing channel quality assessment, we have formulated a composite metric, which we call channel rank measurement (CRM), that can demarcate channels into good, intermediate and bad quality on the basis of the standard deviation of the received signal strength indicator (RSSI) and the average of the link quality indicator (LQI) of the received packets. CRM is then used to generate a data set for training a supervised machine learning-based algorithm (which we call Normal Equation based Channel quality prediction (NEC) algorithm) in such a way that it may perform instantaneous channel rank estimation of any channel. Subsequently, two robust extensions of the NEC algorithm are proposed (which we call Normal Equation based Weighted Moving Average Channel quality prediction (NEWMAC) algorithm and Normal Equation based Aggregate Maturity Criteria with Beta Tracking based Channel weight prediction (NEAMCBTC) algorithm), that can perform channel quality estimation on the basis of both current and past values of channel rank estimation. In the end, simulations are made using MATLAB, and the results show that the Extended version of NEAMCBTC algorithm (Ext-NEAMCBTC) outperforms the compared techniques in terms of channel quality and stability assessment. It also minimizes channel switching overheads (in terms of switching delays and energy consumption) for accommodating stream-based communication in multichannel WSNs.

Robust topology construction method with radio interface constraint for multi-radio multi-channel wireless mesh network using directional antennas

Multi-radio and multi-channel wireless mesh networks using directional antenna (MR-MC DWMN) greatly improve the spatial reuse of wireless channels and increase network capacity. However, the number of directional radio interfaces in MR-MC DWMN affects topology reliability and survivability. This article focuses on the construction of robust topology with radio interface constraints in MR-MC DWMN. Because of the limitation of the number of directional radio interfaces, we first formulate this topology optimization problem with directional radio interface constraints to be equivalent to establish k-connected topology with node degree constraints and then propose a robust topology construction algorithm with directional radio interface constraint. We define the link weight based on node degree and then use graph theory to construct the robust topology with node degree constraints. The proposed constructing robust topology with directional radio interface constraint can not only establish k-connected topology but also minimize the maximum node degree and meet the requirement of radio interface constraints. Simulation shows that constructing robust topology with directional radio interface constraint obtains less maximum node degree and average path length than existing k-connected topology control algorithms under the limitation of directional radio interfaces. Moreover, the constructing robust topology with directional radio interface constraint achieves better network performance than other algorithms.

Who are you? Secure identities in single hop ad hoc networks

Sybil attacks occur when malicious users create multiple fake identities to gain an advantage over honest users. Wireless ad hoc networks are particularly vulnerable to these attacks because the participants are not known in advance, and they use an open and shared communication medium. In this paper, we develop algorithms that can effectively thwart sybil attacks in single hop multi-channel wireless ad hoc networks using radio resource testing strategies. We present and analyze new anti-sybil algorithms for establishing trusted identities, specifically, that guarantee, with high probability, that each honest device accepts a set of trusted and unforgeable identities that include all other honest devices and a bounded number of fake (sybil) identities. The proposed algorithms provide trade-offs between time complexity and sybil bounds. We also note that these algorithms solve, as subroutines, two problems of independent interest in this anonymous wireless setting: Byzantine consensus and network size estimation.

Throughput-Delay Trade-off Scheduling in Multi-channel Downlink Wireless Networks

This paper designs a down-link resource scheduling algorithm for wireless cellular networks to achieve throughput-delay trade-off. The available bandwidth of the down-link is divided into some parallel sub-channels, and each sub-channel can be allocated to one potential user in every time-slot. This problem is modeled as a multi-user multi-server discrete-time queuing system with a time-varying connectivity. For this system, it is well-known that the classical MaxWeight algorithm has the optimal throughput, but its delay performance is very poor. To overcome this issue, we use the Lyapunov Optimization technique to design a throughput-utility maximizing algorithm that provides a good trade-off between the throughput and delay performance. Our approach is verified by both theoretical analysis and simulation evaluations.

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.

Multichannel Wireless Neural Recording AFE Architectures: Analysis, Modeling, and Tradeoffs

This paper presents theoretical analyses of three analog-to-digital-conversion-based and one analog-to-time-conversion-based AFE architectures. They are particularly focused on the significant parameters that affect the design of neural recording implants.

A Fully Integrated Wireless Compressed Sensing Neural Signal Acquisition System for Chronic Recording and Brain Machine Interface.

Reliable, multi-channel neural recording is critical to the neuroscience research and clinical treatment. However, most hardware development of fully integrated, multi-channel wireless neural recorders to-date, is still in the proof-of-concept stage. To be ready for practical use, the trade-offs between performance, power consumption, device size, robustness, and compatibility need to be carefully taken into account. This paper presents an optimized wireless compressed sensing neural signal recording system. The system takes advantages of both custom integrated circuits and universal compatible wireless solutions. The proposed system includes an implantable wireless system-on-chip (SoC) and an external wireless relay. The SoC integrates 16-channel low-noise neural amplifiers, programmable filters and gain stages, a SAR ADC, a real-time compressed sensing module, and a near field wireless power and data transmission link. The external relay integrates a 32 bit low-power microcontroller with Bluetooth 4.0 wireless module, a programming interface, and an inductive charging unit. The SoC achieves high signal recording quality with minimized power consumption, while reducing the risk of infection from through-skin connectors. The external relay maximizes the compatibility and programmability. The proposed compressed sensing module is highly configurable, featuring a SNDR of 9.78 dB with a compression ratio of 8×. The SoC has been fabricated in a 180 nm standard CMOS technology, occupying 2.1 mm × 0.6 mm silicon area. A pre-implantable system has been assembled to demonstrate the proposed paradigm. The developed system has been successfully used for long-term wireless neural recording in freely behaving rhesus monkey.

Toward Optimal Distributed Monitoring of Multi-Channel Wireless Networks

This paper studies an optimal channel assignment problem for passive monitoring in multi-channel wireless networks, where a set of sniffers capture and analyze the network traffic to monitor the wireless network. The objective of this problem is to maximize the total amount of traffic captured by sniffers by judiciously assigning the radios of sniffers to a set of channels. This problem is NP-hard, with the computational complexity growing exponentially with the number of sniffers. We develop distributed online solutions for large-scale and dynamic networks. The dynamism in the network may arise from mobility of the nodes being monitored. Our algorithm is guaranteed to achieve at least $1 - \frac{1}{e}$ times the optimum, regardless of the network topology and the channel assignment of nodes to be monitored, while providing a distributed solution amenable to online implementation. Further, our algorithm is cost-effective, in terms of communication and computational overheads, due to the use of purely local communication and the incremental adaptation to network changes. We present two operational modes of our algorithm for two types of networks that change at different rates; one is a proactive mode for fast-varying networks, while the other is a reactive mode for slowly-varying networks. Simulation results demonstrate the effectiveness of the two modes of our algorithm and compare it to the theoretically optimal algorithm.

Global Optimization for Multi-Channel Wireless Data Broadcast with AH-Tree Indexing Scheme

Multi-channel wireless data broadcast is an appropriate approach to disseminate data to a mass number of mobile clients. In this paper, we present a global optimization for multi-channel wireless data broadcast with Alphabetic Huffman Tree (AH-Tree) Indexing scheme, which can deal with skewed access frequencies well. We present three novel designs to reduce the access latency and tuning time of the broadcast system. Firstly, we design a dynamic programming for AH-Tree construction with low time complexity. Compared with traditional Hu-Tucker algorithm in $O(n^k)$ , our algorithm can build a $k$ -ary AH-Tree index in $O(n^2)$ . Next, we depict a new control table design, which eliminates up to 50 percent redundant entries while keeps the searching efficiency. We also theoretically prove that an optimal alphabetic tree has the minimum average tuning time among all tree-based index structures for skewed data broadcast. Thirdly, we design the new index and data allocation algorithms to further reduce the tuning time and access latency. The simulation results validate the effectiveness of our algorithms. In all, our global optimization mechanism can greatly improve the system performance and time efficiency for wireless data broadcast applications.

A Distributed Opportunistic MAC Protocol for Multichannel Wireless Networks

We propose a distributed opportunistic medium access control (MAC) scheme for maximizing the expected aggregate throughput in a multichannel wireless network such as a clustered orthogonal frequency-division multiple access (OFDMA) network. In our proposed scheme, each user attempts to send only on its best channel and transmits if the best-channel gain is higher than a given threshold, which is dynamically updated depending on previous idle and collision situations. In this way, with our proposed scheme, in a homogeneous system where the channel fading distribution is identical for all users, the best user for each channel is obtained in a distributed manner. We also obtain the optimal values of the thresholds so that the probability of successful transmission is maximized and a minimal number of transmission opportunities are wasted (e.g., due to collision or idle transmissions). In the asymptotic limit of a large number of users and sufficiently long transmission slot duration, we show that, in comparison with the optimal centralized scheme, the throughput loss for our proposed scheme goes to zero. Furthermore, we extend our distributed opportunistic MAC scheme for a homogeneous system to that for a heterogeneous system where the channel fading distribution is heterogeneous across users. Throughput performances and signaling overhead are analyzed for the proposed distributed MAC schemes and compared with those of the existing schemes. Simulation results show that our proposed schemes significantly improve the average aggregate throughput when compared with the existing schemes.

Performance Analysis of Large Multi-Interface Wireless Mesh Networks with Multi-Different Bandwidth Channel

In this paper, we study the asymptotic throughput capacity of a static multi-channel multi-interface infrastructure wireless mesh network (InfWMN) wherein each infrastructure node has m interfaces and c channels of unequal bandwidth are available. First, an upper bound on the InfWMN per-user capacity is established. Then, the feasible lower bound is derived by construction. We prove that both lower and upper bounds are tight. We limit our analysis for more practical case of $\mathrm{m} \le \mathrm{c}$ . However, for the asymptotic upper bound, our analysis can be used for the general case in which there is no constraint on m and c. Our study shows that in such a network with Nc randomly distributed mesh clients, Nr regularly placed mesh routers, and Ng gateways, the asymptotic per-client throughput capacity has different bounds, which depend on the ratio between the total available bandwidth for the network and the sum of m first greatest data rates of c available channels, i.e., $\sum \limits_{\mathrm{j} = 1}^\mathrm{C} \mathrm{w}_\mathrm{j} / \sum \limits_{\mathrm{j} = 1}^\mathrm{m} \mathrm{w}_\mathrm{j}$ . The results of this paper are more general compared to the existing published researches. In addition, in the case that $\mathrm{w}_\mathrm{i} = \mathrm{W}/\mathrm{c} \forall \mathrm{i},\mathrm{}1 \le \mathrm{i} \le \mathrm{c}$ , our results reduce to the previously reported studies. This implies that our study is comprehensive compared to the formerly published researches.

On Demand Stable Routing with Channel Allocation and Backoff Countdown Optimization in Wireless Mesh Networks

The multi-channel and multi-interface wireless mesh networks (WMNs) allow multiple orthogonal channels simultaneously to facilitate increased broadband connectivity to the end-users. Many efforts have been devoted to allocate the channels to the interfaces in a multi-channel multi-interface setting. Recently, the hybrid channel allocation mechanism jointly optimizes the routing and channel assignment, by utilizing the queuing traffic. It is essential to map the optimization of traffic distribution on each channel along with channel switching in such an order that it adapts to the changing traffic. However, the contention in medium access and channel switching delay are the key issues in a multi-channel hidden terminal problem. The proposed optimized stable path- channel allocation and routing (OSCAR) protocol is a hybrid multi-channel protocol that reduces the communication delay without degrading the network performance. The proposed work, OSCAR determines a highly stable path that increases mesh routers to improve the routing efficiency. The channel allocation mechanism mainly promotes queue dynamics based probabilistic channel selection (QDPCS), and backoff countdown optimization (BCO). An essential component of the QDPCS scheme is the factor of queuing utilization, and this strategy selects a least congested channel. The BCO mechanism creates the logical order among contending nodes based on the remaining backoff value. It reduces the medium access delay and enables the feasibility of scheduled transmissions without degrading the network throughput. Finally, the performance evaluation results show that the OSCAR protocol outperforms the existing protocol over WMNs.

Design and Verification of a High-Precision Wireless Strength Testing Node for Aircraft Structure

Wireless sensor network provides a good solution for the state monitoring of large-scale structures. Compared to traditional approaches, it can greatly reduce the amount of devices wiring and the weight of the monitoring system. However, research of aviation structure monitoring application based wireless sensor networks is still in the initiation of the exploration stage. In particular, the developed wireless strain sensor node of WSN cannot be used in aviation structure because of low precision and other problems. In this paper, a high-precision and multichannel wireless strain sensor node of WSN is designed in detail. The wireless strain sensor node is composed of power module, multichannel strain sensing acquisition module, data-processing module, and wireless communication module. In addition, its special design of encapsulation makes it shock-proof and possess anti-interference property. To verify the functionality of the designed wireless sensor node for structural strength testing capability, several evaluation experiments are completed on a test piece of real aircraft. The experimental results show that the developed system has good performance in monitoring structural strain.

Partially overlapped channels- and flow-based end-to-end channel assignment for multi-radio multi-channel wireless mesh networks

Capacity reduction is a major problem faced by wireless mesh networks. An efficient way to alleviate this problem is proper channel assignment. Current end-toend channel assignment schemes usually focus on the case where channels in distinct frequency bands are assigned to mesh access and backbone, but actually backbone network and access network can use the same IEEE 802.11 technology. Besides, these channel assignment schemes only utilize orthogonal channels to perform channel assignment, and the resulting network interference dramatically degrades network performance. Moreover, Internet-oriented traffic is considered only, and peer-to-peer traffic is omitted, or vice versa. The traffic type does not match the practical network. In this paper, we explore how to exploit partially overlapped channels to perform end-to-end channel assignment in order to achieve effective end-to-end flow transmissions. The proposed flow-based end-to-end channel assignment schemes can conquer the limitations aforementioned. Simulations reveal that loadaware channel assignment can be applied to networks with stable traffic load, and it can achieve near-optimal performance; Traffic-irrelevant channel assignment is suitable for networks with frequent change of traffic load, and it can achieve good balance between performance and overhead. Also, partially overlapped channels' capability of improving network performance is situation-dependent, they should be used carefully.

Distributed Joint Rate Control, Resource Allocation, and Congestion Control for Throughput Optimization in Multirate Multiradio Multichannel Wireless Network with Intersession/Intrasession Network Coding

Wireless multihop networks are increasingly used because of their low cost and easy deployment. However, there are still many restrictions that degrade performance. Network coding has been proposed to improve the throughput of a wireless network through the characteristics of overhearing and broadcast. In this paper, we model the network utility maximization problem using a combined intrasession and intersession network coding method to improve the network utility in multiradio, multichannel, and multirate wireless network. And we propose a network throughput optimization scheme with a rate control, resource allocation and congestion control algorithm. We formulate an optimal framework reflecting wireless network environment. Also, we propose a rate selection scheme to choose the transmission rate on each node. We evaluate the proposed algorithms by simulation. The performance evaluation results show that the proposed scheme can improve throughput for network by utility optimization in a multiradio, multichannel, and multirate wireless network.

A cross-layer framework for joint routing and rate adaptation in infrastructure Wireless Mesh Networks

In this paper, we propose a cross-layer framework for joint routing and rate adaptation in multi-rate, Multi-Channel, Multi-Radio (MCMR) infrastructure Wireless Mesh Networks (WMNs). These networks use MCMR capabilities of mesh routers to achieve high performance. However, the MCMR nodes introduce interference in the multi-hop mesh networks and can degrade QoS. Thus, the design of routing metrics to improve the QoS has become an important research issue. Furthermore, as the routing metric and rate adaptation decisions are closely related, the joint approach is needed to improve the performance of the network. Towards this, we analytically derive our routing metric using IEEE 802.11 Distributed Coordination Function (DCF) basic access mechanism. Using this model, we propose Passive Interference and Delay Aware (P-IDA) routing metric which estimates the delay and interference by exploiting cross-layer information. We extend the work by performing joint routing and rate adaptation. The simulation results using NS2 reveal that proposed framework improves throughput and delay compared to existing approaches with reduced routing overhead.

An Efficient Mac Protocol for Reducing Channel Interference and Access Delay in Cognitive Radio Wireless Mesh Networks

With the increase of wireless mesh networks, channel access, bandwidth usage and channel interferences are the major key issues of multi-channel WMNs and MAC specifications. The multi-radio, multi-channel wireless mesh networks (MR-MC-WMNs) are a kind of networks that provide high reliable communication for a large number of mesh nodes. These networks have mesh routers and channels that are stationary and each router or node has multiple channels. Although IEEE 802.11 versions support up to 3 and 12 multiple non-overlapping channels, it is the major challenge of the multichannel environment which exploits all channels to communicate a large volume of network data in WMNs. Cognitive radio users has the capability to access unused portion of the multichannel spectrum. The major interference can be created by CR as well as licensed user. Traditional MAC based operations are implemented using common-control-channel to handle cognitive radio end users. We proposed a new Multi-objective based CMR-MC-WMNs framework using TDMA based MAC protocol to optimize the network performance, channel interference and access delay issues in the network. Experimental results prove that, proposed work has less delay and inference rates compared to traditional models.

A framework to compare topology algorithms in multi-channel multi-radio wireless mesh networks

Creating an optimal topology for a multi-channel multi-radio wireless mesh network by an algorithm is a balancing act between different metrics such as bandwidth, delay, and redundancy. We propose a framework to quickly evaluate and compare resulting network graphs of different topology algorithms, both distributed and centralized, in wireless mesh networks. This framework complements to graph analysis and network simulation. The metrics presented in this paper, are both data flow (such as bandwidth capacity, delay, and loss) and structural characteristics (such as minimal edge and node cut) related. Each presented metric can be solved using a linear programming with the weighted incidence matrix of the network graph and the protocol interference model. The framework uses matrix operations, which are well established, making the framework unambiguous and easy to implement. We demonstrate the framework by comparing topology algorithms with increasing complexity and by comparing topology algorithms found in literature.

A cross-layer approach for multi-layer multicast routing in multi-channel multi-radio wireless mesh networks

In this paper, we consider multicast applications with bandwidth heterogeneous receivers in multi-channel multi-radio wireless mesh networks MC-MR WMNs. Multi-layering is a well-established approach to handle bandwidth heterogeneity of the receivers. Existing multi-layering schemes have addressed only single-channel settings. In the context of MC-MR WMNs, the channel assignment problem is coupled with multicast routing, thus necessitating a cross-layer solution. In this paper, we propose an optimal cross-layer model, which aims at maximising the total number of obtained layers by the receivers. We include network coding in our design to take advantage of its capacity boosting in multicasting. To alleviate time complexity of the optimal model, we propose grouping-based multi-layer multicast GMLMC algorithm, which yields close to optimal throughput, i.e., nearly 96% of the optimum, in polynomial time. Moreover, the pattern of layer reception to the receivers in the outcomes of GMLMC resembles very much to the optimal results.

Learning Automata Based Channel Assignment with Power Control in Multi-Radio Multi-Channel Wireless Mesh Networks

Wireless channel assignment is one of the major challenging issues in multi hop wireless mesh networks (WMN) when there is the need to design them in a distributed fashion, specifically for multi-radio multi-channel (MRMC) systems. In this work, a new learning automata based channel and power assignment scheme which adaptively improve network overall throughput by expecting network dynamics was proposed. First, a utility function which reflected the user’s preference for the signal to interference and noise ratio (SINR) was applied, and then the transmitter power. The distributed channel assignment and power control problem is formulated as a multiple payoff stochastic game of automata. In this game, each user evaluates a channel and power selection strategy by computing a utility value. This evaluation is performed using a stochastic iterative procedure. The utility function that potentially reflected a measure of satisfaction of every node was used by every node as an environmental response for the current selected strategy chosen by the nodes. According to dynamics of system, the proposed algorithm assigned channels and powers to radio interface such that it minimized interference in the neighborhood of a node. The stability of the system was analyzed via appropriate Lyapunov-like trajectory; it was shown that the stability and optimum point of the system converged.