Daru Pan

A comprehensive-integrated buffer management strategy for opportunistic networks

Opportunistic networks aim to provide reliable communications in an intermittently connected environment. The research in cache management of opportunistic networks has been done a lot in those aspects, such as queue strategy, cache replace, redundancy delete, etc. But most of the existing studies only focus on a subdivision of the buffer management. To deal with such case, this article proposes a comprehensive integration buffer management strategy, called comprehensive-integrated buffer management (CIM), which takes all information relevant to message delivery and network resources into consideration. The simulation experiments show that the CIM strategy improved the performance in terms of delivery ratio, overhead ratio, and average delivery delay.

Superimposed training for channel estimation of OFDM modulated amplify-and-forward relay networks

This paper is concerned with the problem of channel estimation for amplify-and-forward (AF) cooperative relay networks with orthogonal frequency division multiplexing (OFDM) modulation. The algorithm is based on both the least square (LS) and minimum mean square error (MMSE) technique with a superimposed training strategy. Specifically, both the source and relay superimpose their own training signal onto data stream prior to transmission so as to estimate the separate channel state information of the source to relay link and the relay to destination link. We also present the performance analysis and derive the approximated closed-form expressions for the MSE of separate channel estimation of source to relay link and the relay to destination link, respectively, from which we compute the optimal training signal as well as the relay power-amplification factor. To further improve the performance of channel estimation, we adopt a weighted average process to enhance the estimation performance over multiple OFDM blocks, from which we compute the optimal tracking factor. Simulation results are provided to corroborate the proposed scheme.

Linearly time-varying channel estimation and training power allocation for OFDM/MIMO systems using superimposed training

We address the problem of estimating the linearly time-varying (LTV) channel of orthogonal frequency division multiplexing (OFDM)/multiple-input multiple-output (MIMO) systems using superimposed training (ST). The LTV channel is modeled by truncated discrete Fourier bases. Based on this model, a two-step approach is adopted to estimate the LTV channel over multiple OFDM symbols. We also present performance analysis of the channel estimation and derive a closed-form expression for the channel estimation variances. It is shown that the estimation variances, unlike that of the conventional ST-based schemes, approach to a fixed lower-bound as the training length increases, which is directly proportional to information-pilot power ratios. For wireless communication systems with a limited transmission power, we optimize the ST power allocation by maximizing the lower bound of the average channel capacity. Simulation results show that the proposed approach outperforms the frequency-division multiplexed training schemes.

Doubly selective channel estimation for OFDM modulated amplify-and-forward relay networks using superimposed training

This article is concerned with the problem of superimposed training (ST)-aided channel estimation for orthogonal frequency division multiplexingmodulated amplify-and-forward relay networks in doubly selective environment. A ‘subblockwise’ linear assumption-based channel model is proposed to represent the mobile-to-mobile time- and frequency-selective channels. We then propose a novel ST strategy that allows the destination node to separately obtain the channel information of the source → relay link and the relay → destination link, from which the optimal ST signals are derived by minimizing the channel mean-square-error. To enhance the performance of channel estimation, a subblock tracking-based low-complexity decision feedback approach is introduced to iteratively mitigate the unknown data interference. Finally, extensive numerical results are provided to corroborate the proposed studies.

Buffer management for streaming media transmission in hierarchical data of opportunistic networks

An opportunistic network is a kind of novel and self-organizing mobility network with DTN (Delay Tolerant Networks) features, which has no fixed topological structure and transfers messages using the opportunity of nodes encountering. Transmitting steaming media in such a network faces significant challenge, since the topology between source node and destination node is variable. In order to increase the delivery ratio, an opportunistic network employs the message redundancy mechanism, which leads to the existing of multiple copies of messages in different routes at the same moment. These duplicates tend to jam the network, block later messages and jeopardize network performance due to the limited buffer resource of nodes. In this context, we propose a novel buffer management algorithm for streaming media (BMSM) in an opportunistic network by combining the characters of opportunistic networks with the feature of hierarchical data encoding of H.264 streaming media. The BMSM algorithm fully utilizes the real-time dynamic parameters of the network, i.e., remaining living time and the estimation of message copies, and it automatically assigns a priority parameter to a message to determine its transitivity and priority in the nodes buffer sequence based on the hierarchical property of the messages. By combining the mobility of nodes, a new queuing strategy for managing the buffer is also proposed in BMSM, in which a message is forwarded preferentially to the interacting closely truck nodes when it is at the head of the sequence. Simulation results show that the proposed BMSM algorithm effectively improves the delivery rate and limited the network overhead ratio and thereby ensures the continuous media streams.

Equalisation technique for high mobility OFDM-based device-to-device communications using subblock tracking

This study presents a ‘subblock tracking’ based equalisation technique for orthogonal frequency division multiplexing (OFDM) based device-to-device communications over high mobility environment. This technique is to use a rectangular-shaped receive window to partition the OFDM block into subblocks rendering the channel response of each subblock to be time-invariant, thereby allowing one to equalise the channel frequency response on each subcarrier of the subblocks simply by a single tap. The equalised signals are then combined to give the final output, where the combination weights are designed to minimise detection errors. The authors mathematically characterise the detection performance by deriving the signal-to-interference ratio as a function of channel-time-variation and the numbers of subblocks. To further enhance the proposed design without imposing computational consumption, a subblock tracking scheme with partially overlapped partition is presented and theoretically analysed. Simulation results demonstrate the advantages this method over the conventional schemes in high mobility environment.

Time-varying channel estimation for MIMO/OFDM systems using superimposed training and basis expansion models

This paper deals with the problem of time-varying (TV) channel estimation for multiple-input multiple-output/orthogonal frequency-division multiplexing (MIMO/OFDM) systems based on superimposed training (ST). The time-varying coefficients of the TV channel are firstly modeled by truncated discrete Fourier bases, and then optimally estimated both in one OFDM symbols and over multiple OFDM symbols by judiciously designing the superimposed pilots. In addition, an iterative symbol detection based channel estimation scheme with analytical performance analysis, is provided to mitigate the interference due to the unknown information sequences (thus to further improve channel estimation performance as well as SER levels). Simulations confirm that the proposed estimator achieves a considerable gain in estimating TV channels, and exhibits a nearly indistinguishable symbol error rate performance from the OFDM systems of frequency-division multiplexed trainings.

Superimposed Training-Aided Channel Estimation for Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing Systems over High-Mobility Environment

The combination of multiple-input multiple-output (MIMO) antennas and orthogonal frequency-division multiplexing (OFDM) can achieve a lower error rate and/or enable highcapacity wireless communication systems by flexibly exploiting diversity gain and/or the spatial multiplexing gains. Such systems, however, rely upon the knowledge of propagation channels. In many mobile communication systems, transmission is impaired by both delay and Doppler spreads [1]-[7]. In such cases, explicit incorporation of the time-varying characteristics of mobile wireless channel is called for.

Iterative intercarrier interference reduction for mobile OFDM systems

For mobile applications of Orthogonal Frequency-Division Multiplexing (OFDM) systems, channel time-variations during one OFDM symbol interval results in the loss of orthogonality among subcarriers, and thus leading to intercarrier interference (ICI). This paper addresses the problem of ICI reduction for mobile OFDM systems. By rearranging the frequency-domain channel matrix, ICI can be effectively reduced by half at each iterative procedure. The advantages of the proposed scheme are shown through simulations.