The ability of robots to estimate their location is crucial for a wide variety of autonomous operations. In settings where GPS is unavailable, measurements of transmissions from fixed beacons provide an effective means of estimating a robot's location as it navigates. The accuracy of such a beacon-based localization system depends both on how beacons are distributed in the environment, and how the robot's location is inferred based on noisy and potentially ambiguous measurements. We propose an approach for making these design decisions automatically and without expert supervision, by explicitly searching for the placement and inference strategies that, together, are optimal for a given environment. Since this search is computationally expensive, our approach encodes beacon placement as a differential neural layer that interfaces with a neural network for inference. This formulation allows us to employ standard techniques for training neural networks to carry out the joint optimization. We evaluate this approach on a variety of environments and settings, and find that it is able to discover designs that enable high localization accuracy.
The above methods address spatial placement but not transmission channel assignments, and associated issues with interference. Automatic channel assignment methods have been considered previously, but only for optimizing communication throughput @cite_10 @cite_16 --- to minimize interference from two beacons in the same channel at any location. Note that this is a very different and simpler objective than one of enabling accurate localization, where the goal is to ensure that there is a unique mapping from every RSS signature (with or without interference) to location.
@cite_16 @cite_10
2035804590 2152465511
The capacity problem in wireless mesh networks can be alleviated by equipping the mesh routers with multiple radios tuned to non-overlapping channels. However, channel assignment presents a challenge because co-located wireless networks are likely to be tuned to the same channels. The resulting increase in interference can adversely affect performance. This paper presents an interference-aware channel assignment algorithm and protocol for multi-radio wireless mesh networks that address this interference problem. The proposed solution intelligently assigns channels to radios to minimize interference within the mesh network and between the mesh network and co-located wireless networks. It utilizes a novel interference estimation technique implemented at each mesh router. An extension to the conflict graph model, the multi-radio conflict graph, is used to model the interference between the routers. We demonstrate our solution’s practicality through the evaluation of a prototype implementation in a IEEE 802.11 testbed. We also report on an extensive evaluation via simulations. In a sample multi-radio scenario, our solution yields performance gains in excess of 40 compared to a static assignment of channels. Multichannel communication in a wireless mesh network with routers having multiple radio interfaces significantly enhances the network capacity. Efficient channel assignment and routing is critical for realization of optimal throughput in such networks. In this paper, we investigate the problem of finding the largest number of links that can be activated simultaneously in a wireless mesh network subject to interference, radio and connectivity constraints. Our goal is to activate all such links and we present an interference aware channel assignment algorithm that realizes this goal. We show that the Link Interference Graph created by utilizing a frequently used interference model gives rise to a special class of graphs, known as overlapping double-disk (ODD) graphs. We prove that the Maximum Independent Set computation problem is NP-complete for this special class of graphs. We provide a Polynomial Time Approximation Scheme (PTAS) for computation of the Maximum Independent Set of an ODD graph. We use this PTAS to develop a channel assignment algorithm for a multiradio multichannel Wireless Mesh Network. We evaluate the performance of our channel assignment algorithm by comparing it with the optimal solution obtained by solving an integer linear program. Experimental results demonstrate that our channel assignment algorithm produces near optimal solution in almost all instances of the problem. The throughput of wireless networks can be significantly improved by multi-channel communications compared with single-channel communications since the use of multiple channels can reduce interference influence. In this paper, we study interference-aware topology control and QoS routing in IEEE 802.11-based multi-channel wireless mesh networks with dynamic traffic. Channel assignment and routing are two basic issues in such networks. Different channel assignments can lead to different network topologies. We present a novel definition of co-channel interference. Based on this concept, we formally define and present an effective heuristic for the minimum INterference Survivable Topology Control (INSTC) problem which seeks a channel assignment for the given network such that the induced network topology is interference-minimum among all K-connected topologies. We then formulate the Bandwidth-Aware Routing (BAR) problem for a given network topology, which seeks routes for QoS connection requests with bandwidth requirements. We present a polynomial time optimal algorithm to solve the BAR problem under the assumption that traffic demands are splittable. For the non-splittable case, we present a maximum bottleneck capacity path routing heuristic. Simulation results show that compared with the simple common channel assignment and shortest path routing approach, our scheme improves the system performance by 57 on average in terms of connection blocking ratio. Multihop infrastructure wireless mesh networks offer increased reliability, coverage, and reduced equipment costs over their single-hop counterpart, wireless local area networks. Equipping wireless routers with multiple radios further improves the capacity by transmitting over multiple radios simultaneously using orthogonal channels. Efficient channel assignment and routing is essential for throughput optimization of mesh clients. Efficient channel assignment schemes can greatly relieve the interference effect of close-by transmissions; effective routing schemes can alleviate potential congestion on any gateways to the Internet, thereby improving per-client throughput. Unlike previous heuristic approaches, we mathematically formulate the joint channel assignment and routing problem, taking into account the interference constraints, the number of channels in the network, and the number of radios available at each mesh router. We then use this formulation to develop a solution for our problem that optimizes the overall network throughput subject to fairness constraints on allocation of scarce wireless capacity among mobile clients. We show that the performance of our algorithms is within a constant factor of that of any optimal algorithm for the joint channel assignment and routing problem. Our evaluation demonstrates that our algorithm can effectively exploit the increased number of channels and radios, and it performs much better than the theoretical worst case bounds Sensor networks operating in the 2.4 GHz band often face cross-technology interference from co-located WiFi and Bluetooth devices. To enable effective interference mitigation, a sensor network needs to know the type of interference it is exposed to. However, existing approaches to interference detection are not able to handle multiple concurrent sources of interference. In this paper, we address the problem of identifying multiple channel activities impairing a sensor network’s communication, such as simultaneous WiFi traffic and Bluetooth data transfers. We present SpeckSense, an interference detector that distinguishes between different types of interference using a unsupervised learning technique. Additionally, SpeckSense features a classifier that distinguishes between moderate and heavy channel traffic, and also identifies WiFi beacons. In doing so, it facilitates interference avoidance through channel blacklisting. We evaluate SpeckSense on common mote hardware and show how it classifies concurrent interference under real-world settings. We also show how SpeckSense improves the performance of an existing multichannel data collection protocol by 30 . Compared to single-hop networks such as WiFi, multihop infrastructure wireless mesh networks (WMNs) can potentially embrace the broadcast benefits of a wireless medium in a more flexible manner. Rather than being point-to-point, links in the WMNs may originate from a single node and reach more than one other node. Nodes located farther than a one-hop distance and overhearing such transmissions may opportunistically help relay packets for previous hops. This phenomenon is called opportunistic overhearing listening. With multiple radios, a node can also improve its capacity by transmitting over multiple radios simultaneously using orthogonal channels. Capitalizing on these potential advantages requires effective routing and efficient mapping of channels to radios (channel assignment (CA)). While efficient channel assignment can greatly reduce interference from nearby transmitters, effective routing can potentially relieve congestion on paths to the infrastructure. Routing, however, requires that only packets pertaining to a particular connection be routed on a predetermined route. Random network coding (RNC) breaks this constraint by allowing nodes to randomly mix packets overheard so far before forwarding. A relay node thus only needs to know how many packets, and not which packets, it should send. We mathematically formulate the joint problem of random network coding, channel assignment, and broadcast link scheduling, taking into account opportunistic overhearing, the interference constraints, the coding constraints, the number of orthogonal channels, the number of radios per node, and fairness among unicast connections. Based on this formulation, we develop a suboptimal, auction-based solution for overall network throughput optimization. Performance evaluation results show that our algorithm can effectively exploit multiple radios and channels and can cope with fairness issues arising from auctions. Our algorithm also shows promising gains over traditional routing solutions in which various channel assignment strategies are used. This paper considers the interaction between channel assignment and distributed scheduling in multi-channel multi-radio Wireless Mesh Networks (WMNs). Recently, a number of distributed scheduling algorithms for wireless networks have emerged. Due to their distributed operation, these algorithms can achieve only a fraction of the maximum possible throughput. As an alternative to increasing the throughput fraction by designing new algorithms, we present a novel approach that takes advantage of the inherent multi-radio capability of WMNs. We show that this capability can enable partitioning of the network into subnetworks in which simple distributed scheduling algorithms can achieve 100 throughput. The partitioning is based on the notion of Local Pooling. Using this notion, we characterize topologies in which 100 throughput can be achieved distributedly. These topologies are used in order to develop a number of centralized channel assignment algorithms that are based on a matroid intersection algorithm. These algorithms pre-partition a network in a manner that not only expands the capacity regions of the subnetworks but also allows distributed algorithms to achieve these capacity regions. We evaluate the performance of the algorithms via simulation and show that they significantly increase the distributedly achievable capacity region. We note that while the identified topologies are of general interference graphs, the partitioning algorithms are designed for networks with primary interference constraints. We propose and investigate a compressive architecture for estimation and tracking of sparse spatial channels in millimeter (mm) wave picocellular networks. The base stations are equipped with antenna arrays with a large number of elements (which can fit within compact form factors because of the small carrier wavelength) and employ radio frequency (RF) beamforming, so that standard least squares adaptation techniques (which require access to individual antenna elements) are not applicable. We focus on the downlink, and show that “compressive beacons,” transmitted using pseudorandom phase settings at the base station array, and compressively processed using pseudorandom phase settings at the mobile array, provide information sufficient for accurate estimation of the two-dimensional (2D) spatial frequencies associated with the directions of departure of the dominant rays from the base station, and the associated complex gains. This compressive approach is compatible with coarse phase-only control, and is based on a near-optimal sequential algorithm for frequency estimation which approaches the Cramer Rao Lower Bound. The algorithm exploits the geometric continuity of the channel across successive beaconing intervals to reduce the overhead to less than 1 even for very large ( @math ) arrays. Compressive beaconing is essentially omnidirectional, and hence does not enjoy the SNR and spatial reuse benefits of beamforming obtained during data transmission. We therefore discuss system level design considerations for ensuring that the beacon SNR is sufficient for accurate channel estimation, and that inter-cell beacon interference is controlled by an appropriate reuse scheme. Next generation fixed wireless broadband networks are being increasingly deployed as mesh networks in order to provide and extend access to the internet. These networks are characterized by the use of multiple orthogonal channels and nodes with the ability to simultaneously communicate with many neighbors using multiple radios (interfaces) over orthogonal channels. Networks based on the IEEE 802.11a b g and 802.16 standards are examples of these systems. However, due to the limited number of available orthogonal channels, interference is still a factor in such networks. In this paper, we propose a network model that captures the key practical aspects of such systems and characterize the constraints binding their behavior. We provide necessary conditions to verify the feasibility of rate vectors in these networks, and use them to derive upper bounds on the capacity in terms of achievable throughput, using a fast primal-dual algorithm. We then develop two link channel assignment schemes, one static and the other dynamic, in order to derive lower bounds on the achievable throughput. We demonstrate through simulations that the dynamic link channel assignment scheme performs close to optimal on the average, while the static link channel assignment algorithm also performs very well. The methods proposed in this paper can be a valuable tool for network designers in planning network deployment and for optimizing different performance objectives. A scheme for two-hop relay-assisted cooperative communications integrated with transmit power control, based on simple channel prediction, is presented. A large set of empirical on- and inter-body channel data is employed to model various scenarios of wireless body area network (WBAN) communica- tions, from one isolated WBAN up to 10 closely located WBANs coexisting. Our study shows that relay assisted power control can reduce approximately 60 circuit power consumption from that of constant transmission at 0 dBm, without much loss in reliability. Further, interference mitigation is significantly enhanced over constant transmission at −5 dBm, with similar power consumption. Such performance is maintained from 2 to 10 closely-located WBANs coexisting. And the joint algorithm works best for one isolated WBAN. A trade-off between power saving and interference mitigation is motivated, taking remaining sensor-battery level, amount of interference and on-body channel quality into account. Index Terms—Cooperative communications, interference mit- igation, transmit power control, wireless body area networks. A multi-channel parallel transmission protocol is proposed for the medium access control in cognitive radio networks (CRNs). This protocol contains two key elements: multi-channel assignment and multi-channel contention. For an incoming flow-based connection request, the minimum number of parallel channels are assigned to satisfy the rate and interference mask constraints. For the contention of the assigned channels, our protocol provides an extension of the single-channel RTS- CTS-DATA-ACK handshaking of the IEEE 802.11 scheme. The proposed MAC coherently integrates optimization results into a practical implementation. Through numerical examples, we verify that our protocol provides lower connection blocking probability and higher system throughput for CRNs than its single-channel counterpart. We address device-to-device (D2D) communication as a potential resource reuse technique underlaying the cellular network. We consider the shared channel of the two systems as an interference channel and formulate the statistics of the signal to interference plus noise ratio (SINR) of all users. The potential performance of D2D communication is evaluated by considering a scenario where only limited interference coordination between the cellular and the D2D communication is possible. We apply a simple power control method to the D2D communication which constrains the SINR degradation of the cellular link to a certain level. Results show that the SINR statistics of the D2D users is comparable to that of the cellular user in most of the cell area. Scheduling gain is possible by properly assigning either of the downlink (DL) or the uplink (UL) resources to the D2D communication. An algorithm to reduce congestion and balance users' load in IEEE 802.11b g Wireless Local Area Networks (WLANs) is presented, which takes into account overlapping channel interference between Access Points (APs) and the signal-to-interference ratio (SIR) experienced by the users. After finding the best channel assignment at the APs, the algorithm then finds the Most Congested Access Point (MCAP). It reexamines the users' association with APs by minimizing the congestion at the MCAP. Simulation results show that the proposed algorithm is capable of significantly reducing the overall congestion in the WLAN while mitigating channel interference. Our algorithm has also been shown to be scalable and it performs well for networks of different topologies. Built upon a shared wireless medium, wireless network is particularly vulnerable to jamming attacks. The ability to recover from attacks and maintain an acceptable level of service degradation is a crucial aspect in the design of a wireless network. To address this issue, this paper investigates the network restoration solutions via the joint design of traffic rerouting, channel re-assignment, and scheduling. Efficient routing and channel assignment schemes can relieve the interference caused by both the normal network nodes and the jamming nodes. Therefore, based on the necessary conditions of schedulability, we first formulate the optimal network restoration problem as linear programming problem, which gives an upper bound on the achievable network throughput. After we solve the LP problems, we have a set of flows assigned to edges that have been assigned to different channels. And based on the LP solutions, we provide a greedy scheduling algorithm using dynamic channel assignment, which schedules both the network traffic and the jamming traffic. In particular, we consider two strategies, namely global restoration and local restoration, which can support a range of tradeoffs between the restoration latency and network throughput after restoration. To quantitatively evaluate the impact of jamming attacks during and after restoration, we define two performance degradation indices, transient disruption index (TDI) and throughput degradation index (THI). Finally, extensive performance evaluations are performed to study the impact of various jamming scenarios in a multi-hop multi-channel wireless network. A Gaussian broadcast channel (GBC) with r single-antenna receivers and t antennas at the transmitter is considered. Both transmitter and receivers have perfect knowledge of the channel. Despite its apparent simplicity, this model is, in general, a nondegraded broadcast channel (BC), for which the capacity region is not fully known. For the two-user case, we find a special case of Marton's (1979) region that achieves optimal sum-rate (throughput). In brief, the transmitter decomposes the channel into two interference channels, where interference is caused by the other user signal. Users are successively encoded, such that encoding of the second user is based on the noncausal knowledge of the interference caused by the first user. The crosstalk parameters are optimized such that the overall throughput is maximum and, surprisingly, this is shown to be optimal over all possible strategies (not only with respect to Marton's achievable region). For the case of r>2 users, we find a somewhat simpler choice of Marton's region based on ordering and successively encoding the users. For each user i in the given ordering, the interference caused by users j>i is eliminated by zero forcing at the transmitter, while interference caused by users j<i is taken into account by coding for noncausally known interference. Under certain mild conditions, this scheme is found to be throughput-wise asymptotically optimal for both high and low signal-to-noise ratio (SNR). We conclude by providing some numerical results for the ergodic throughput of the simplified zero-forcing scheme in independent Rayleigh fading. Abstract Suppose G is a graph and T is a set of nonnegative integers. A T -coloring of G is an assignment of a positive integer ƒ( x ) to each vertex x of G so that if x and y are joined by an edge of G , then |ƒ(x) - ƒ(y)ƒ| is not in T . T -colorings were introduced by Hale in connection with the channel assignment problem in communications. Here, the vertices of G are transmitters, an edge represents interference, ƒ( x ) is a television or radio channel assigned to x , and T is a set of disallowed separations for channels assigned to interfering transmitters. One seeks to find a T -coloring which minimizes either the number of different channels ƒ( x ) used or the distance between the smallest and largest channel. This paper surveys the results and mentions open problems concerned with T -colorings and their variations and generalizations. In this paper, we address the problem of gateway placement for throughput optimization in multi-hop wireless mesh networks. Assume that each mesh node in the mesh network has a traffic demand. Given the number of gateways to be deployed (denoted by k) and the interference model in the network, we study where to place exactly k gateways in the mesh network such that the total throughput is maximized while it also ensures a certain fairness among all mesh nodes. We propose a novel grid-based gateway deployment method using a cross-layer throughput optimization, and prove that the achieved throughput by our method is a constant times of the optimal. Simulation results demonstrate that our method can effectively exploit the available resources and perform much better than random and fixed deployment methods. In addition, the proposed method can also be extended to work with multi-channel and multi-radio mesh networks under different interference models. Most cellular radio systems provide for the use of transmitter power control to reduce cochannel interference for a given channel allocation. Efficient interference management aims at achieving acceptable carrier-to-interference ratios in all active communication links in the system. Such schemes for the control of cochannel interference are investigated. The effect of adjacent channel interference is neglected. As a performance measure, the interference (outage) probability is used, i.e., the probability that a randomly chosen link is subject to excessive interference. In order to derive upper performance bounds for transmitter power control schemes, algorithms that are optimum in the sense that the interference probability is minimized are suggested. Numerical results indicate that these upper bounds exceed the performance of conventional systems by an order of magnitude regarding interference suppression and by a factor of 3 to 4 regarding the system capacity. The structure of the optimum algorithm shows that efficient power control and dynamic channel assignment algorithms are closely related. > In this paper, coexistence of multiple mobile wireless body area networks (WBANs), where there is no coordination between WBANs, is investigated for the case where the WBAN-of-interest employs cooperative communications. A decode-and-forward protocol with two dual-hop links, two relays and selection combining (SC) at the hub (or gateway device) is chosen for the WBAN-of-interest. A suitable time-division-multiple-access (TDMA) scheme is used, enabling intra-network and inter-network operation, to allocate slots for each Tx Rx link packet transmission. Realistic channel models are employed with various amounts of shadowing, small-scale fading and white noise introduced between WBANs. For the WBAN-of-interest, many hours of measured channel gain data is employed to emulate the channel for this WBAN. It is found that the chosen cooperative communications provides significantly better co-channel interference mitigation than single-link star topology WBAN communications in a mobile, dynamic, scenario, hence the signal-to-interference-plus-noise ratio (SINR) for 10 outage probability at the hub is greatly improved by up-to 12 dB. It is also demonstrated that the location of the hub, given three typical locations, has significant impact on the performance of the cooperative WBAN communications. We consider a relay channel in the presence of interference which is non-causally available only at the source. The interference signal may have structure, for example it could come from another source communicating with its own destination. However, the external interferer is not willing to adjust its communication strategy to minimize the interference and is considered to be fixed. Two approaches are possible to mitigate the interference: exploiting the structure or treating the interference as unstructured. Using these approaches, we establish bounds for the Gaussian relay channel with orthogonal components and discuss to the importance of exploiting the interference structure in multi-terminal scenarios.