The characteristics of wireless communication channels may vary with time due to fading, environmental changes and movement of mobile wireless devices. Tracking and estimating channel gains of wireless channels is therefore a fundamentally important element of many wireless communication systems. In particular, the receivers in many wireless networks need to estimate the channel gains by means of a training sequence. This paper studies the scaling law (on the network size) of the overhead for channel gain monitoring in wireless network. We first investigate the scenario in which a receiver needs to track the channel gains with respect to multiple transmitters. To be concrete, suppose that there are n transmitters, and that in the current round of channel-gain estimation, no more than k channels suffer significant variations since the last round. We proves that " (k ((n+1) k)) time slots" is the minimum number of time slots needed to catch up with the k varied channels. At the same time, we propose a novel channel-gain monitoring scheme named ADMOT to achieve the overhead lower-bound. ADMOT leverages recent advances in compressive sensing in signal processing and interference processing in wireless communication, to enable the receiver to estimate all n channels in a reliable and computationally efficient manner within O(k ((n+1) k)) time slots. To our best knowledge, all previous channel-tracking schemes require (n) time slots regardless of k. Note that based on above results for single receiver scenario, the scaling law of general setting is achieved in which there are multiple transmitters, relay nodes and receivers.
(a) Channel monitoring in wireless networks . The works @cite_2 @cite_13 @cite_0 @cite_16 @cite_7 designed probing data and estimation algorithm for estimating channel gains, and the works @cite_29 @cite_14 proposed schemes to estimate channel interference. In the first set of works (which are related to our work), interference has not been shown to be an advantage (compared with nonoverlapping probing signals by different transmitters), and the overhead achieved is @math . Note that in the domain of wireless network coding communication , the work @cite_30 was the first to show the advantage of interference, and later the work @cite_26 proposed an amplify-and-forward relaying strategy for easy implementation.
@cite_30 @cite_14 @cite_26 @cite_7 @cite_29 @cite_0 @cite_2 @cite_16 @cite_13
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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. Traditionally, interference is considered harmful. Wireless networks strive to avoid scheduling multiple transmissions at the same time in order to prevent interference. This paper adopts the opposite approach; it encourages strategically picked senders to interfere. Instead of forwarding packets, routers forward the interfering signals. The destination leverages network-level information to cancel the interference and recover the signal destined to it. The result is analog network coding because it mixes signals not bits. So, what if wireless routers forward signals instead of packets? Theoretically, such an approach doubles the capacity of the canonical 2-way relay network. Surprisingly, it is also practical. We implement our design using software radios and show that it achieves significantly higher throughput than both traditional wireless routing and prior work on wireless network coding. We design pilot-symbol-assisted modulation for carrier frequency offset (CFO) and channel estimation in orthogonal frequency-division multiplexing transmissions over multi-input multi-output frequency-selective fading channels. The CFO and channel-estimation tasks rely on null-subcarrier and nonzero pilot symbols that we insert and hop from block to block. Because we separate CFO and channel estimation from symbol detection, the novel training patterns lead to further decoupled CFO and channel estimators. The performance of our algorithms is investigated analytically, and then compared with an existing approach by simulations. The problems of channel estimation and multiuser detection for direct sequence code division multiple access (DS CDMA) systems employing long spreading codes are considered. With regard to channel estimation, several procedures are proposed based on the least-squares approach, relying on the transmission of known training symbols but not requiring any timing synchronization. In particular, algorithms suited for the forward and reverse links of a single-rate DS CDMA cellular system are developed, and the case of a multirate multicode system, wherein high-rate users are split into multiple virtual low-rate users, is also considered. All of the proposed procedures are recursively implementable with a computational complexity that is quadratic in the processing gain, with regard to the issue of multiuser detection, an adaptive serial interference cancellation (SIC) receiver is considered, where the adaptivity stems from the fact that it is built upon the channel estimates provided by the estimation algorithm. Simulation results show that coupling the proposed estimation algorithms with a SIC receiver may yield, with a much lower computational complexity, performance levels close to those of the ideal linear minimum mean square error (MMSE) receiver, which assumes perfect knowledge of the channels for all of the users and which (in a long-code scenario) has a computational complexity per symbol interval proportional to the third power of the processing gain. The problem of estimating the channel parameters of a new user in a multiuser code-division multiple-access (CDMA) communication system is addressed. It is assumed that the new user transmits training data over a slowly fading multipath channel. The proposed algorithm is based on maximum-likelihood estimation of the channel parameters. First, an asymptotic expression for the likelihood function of channel parameters is derived and a re-parametrization of this likelihood function is proposed. In this re-parametrization, the channel parameters are combined into a discrete time channel filter of symbol period length. Then, expectation-maximization algorithm and alternating projection algorithm-based techniques are considered to extract channel parameters from the estimated discrete channel filter, to maximize the derived asymptotic likelihood function. The performance of the proposed algorithms is evaluated through simulation studies. In addition, the proposed algorithms are compared to previously suggested subspace techniques for multipath channel estimation. A critical issue in applications involving networks of wireless sensors is their ability to synchronize, and mitigate the fading propagation channel effects. Especially when distributed “slave” sensors (nodes) reach-back to communicate with the “master” sensor (gateway), low power cooperative schemes are well motivated. Viewing each node as an antenna element in a multi-input multi-output (MIMO) multi-antenna system, we design pilot patterns to estimate the multiple carrier frequency offsets (CFO), and the multiple channels corresponding to each node-gateway link. Our novel pilot scheme consists of non-zero pilot symbols along with zeros, which separate nodes in a time division multiple access (TDMA) fashion, and lead to low complexity schemes because CFO and channel estimators per node are decoupled. The resulting training algorithm is not only suitable for wireless sensor networks, but also for synchronization and channel estimation of single- and multi-carrier MIMO systems. We investigate the performance of our estimators analytically, and with simulations. We consider correlated MIMO multiple access channels with block fading, where each block is divided into training and data transmission phases. We find the channel estimation and data transmission parameters that jointly optimize the achievable data rate of the system. Our results for the training phase are particularly interesting, where we show that the optimum training signals of the users should be non-overlapping in time. For the data transmission phase, we propose an iterative algorithm that updates the parameters of the users in a round-robin fashion. In particular, the algorithm updates the training and data transmission parameters of a user, when those of the rest of the users are fixed, in a way to maximize the achievable sum-rate in a multiple access channel; and iterates over users in a round-robin fashion.