We propose a geometric mean decomposition (GMD) based vector precoding (VP) for multiple input multiple output (MIMO) systems. Minimum mean square error (MMSE) criterion is used for the joint VP design. The application of GMD method eliminates the imbalance among subchannel gains and obtains a better perturbation vector than the conventional method. We then exploit the extended channel matrix for further performance improvement. Simulation results show the proposed schemes significantly outperform the existing VP schemes.

Constrained by quality-of-service (QoS), a robust transceiver design is proposed for multiple-input multiple-output (MIMO) interference channels with imperfect channel state information (CSI) under bounded error model. The QoS measurement is represented as the signal-to-interference-plus-noise ratio (SINR) for each user with single data stream. The problem is formulated as sum power minimization to reduce the total power consumption for energy efficiency. In a centralized manner, alternating optimization is performed at each node. For fixed transmitters, closed-form expression for the receive beamforming vectors is deduced. And for fixed receivers, the sum-power minimization problem is recast as a semi-definite program form with linear matrix inequalities constraints. Simulation results demonstrate the convergence and robustness of the proposed algorithm, which is important for practical applications in future wireless networks.

Due to the fast advances in wireless networking technology, there is an increasing number of hosts using TCP/IP to connect to the Internet via wireless links. However, it is known that TCP performs poorly on paths with wireless links. This paper presents an approach to address the problem. In the proposed approach, a sender controls the size of transmitted packets and observes the number of losses for each of the controlled packet sizes. It then estimates the number of congestion losses and random losses separately. The results are used to decide whether to reduce the window size or not when a packet loss is detected. We use ns-2 simulator to evaluate the proposed approach. The simulation results show that the proposed approach is able to achieve between 25% and 150% better throughput than FACK under the byte-error rate range of 510-5 to 2010-5.

The effect of the hidden terminal (HT) over multi-hop cascaded wireless networks with the omni-directional full-duplex relays will cause data collision. We allocate the frequency band among different hops in an orthogonal way based on link grouping strategy to avoid this HT problem. In order to maximize the achievable rate, an optimal frequency allocation scheme is proposed by boundary alignment. Performance analyses are provided and further validated by the simulation results.

To improve the performance of underwater acoustic communications, this letter proposes a polar coding scheme with adaptive channel equalization, which can reduce the amount of feedback information. Furthermore, a hybrid automatic repeat request (HARQ) mechanism is provided to mitigate the impact of estimation errors. Simulation results show that the proposed scheme outperforms the turbo equalization in bit error rate. Computational complexity analysis is also provided for comparison.

For suppressing inter symbol interference, the support vector machine mutliuser detector (SVM-MUD) was adopted as a nonlinear method in direct sequence code division multiple access (DS-CDMA) signals transmitted through multipath channels. To solve the problems of the complexity of SVM-MUD model and the number of support vectors, based on recursive least squares support vector machine (RLS-SVM) and Riemannian geometry, a new algorithm for nonlinear multiuser detector is proposed. The algorithm introduces the forgetting factor to get the support vectors at the first training samples, then, uses Riemannian geometry to train the support vectors again and gets less improved support vectors. Simulation results illustrated that the algorithm simplifies SVM-MUD model at the cost of only a little more bit error rate and decreases the computational complexity. At the same time, the algorithm has an excellent effect on suppressing multipath interference.

A new wideband signal DOA estimation algorithm based on modified quantum genetic algorithm (MQGA) is proposed in the presence of the errors and the mutual coupling between array elements. In the algorithm, the narrowband signal subspace fitting method is generalized to wideband signal DOA finding according to the character of space spectrum of wideband signal, and so the rule function is constructed. Then, the solutions is encoded onto chromosomes as a string of binary sequence, the variable quantum rotation angle is defined according to the distribution of optimization solutions. Finally, we use the MQGA algorithm to solve the nonlinear global azimuths optimization problem, and get optimization azimuths by fitness values. The computer simulation results illustrated that the new algorithm have good estimation performance.

In this letter, a method of wideband direction of arrival (DOA) estimation based on co-prime arrays with sub-Nyquist sampling is proposed. Previous works have employed co-prime arrays for wideband DOA estimation, which can increase the degrees of freedom (DOFs) in the spatial domain. However, they are all based on Nyquist sampling. Different from existing methods, we incorporate a sub-Nyquist sampling scheme called multicoset sampling for DOA estimation to relax hardware condition. Simulation results show the correctness and effectiveness.

Much research which has shown the usage of social ties could improve the location predictive performance, but as the strength of social ties is varying constantly with time, using the movement data of user's close friends at different times could obtain a better predictive performance. A hybrid Markov location prediction algorithm based on dynamic social ties is presented. The time is divided by the absolute time (week) to mine the long-term changing trend of users' social ties, and then the movements of each week are projected to the workdays and weekends to find the changes of the social circle in different time slices. The segmented friends' movements are compared to the history of the user with our modified cross-sample entropy to discover the individuals who have the relatively high similarity with the user in different time intervals. Finally, the user's historical movement data and his friends' movements at different times which are assigned with the similarity weights are combined to build the hybrid Markov model. The experiments based on a real location-based social network dataset show the hybrid Markov location prediction algorithm could improve 15% predictive accuracy compared with the location prediction algorithms that consider the global strength of social ties.

Interference alignment (IA) in temporal domain is important in the case of single-antenna vehicle communications. In this paper, perfect cyclic IA based on propagation delay is extended to the K×2 X channels with two receivers and arbitrary transmitters K≥2, which achieves the maximal multiplexing gain by obtaining the theoretical degree of freedom of 2K/(K+1). We deduce the alignment and separability conditions, and propose a general scheme which is flexible in setting the index of time-slot for IA at the receiver side. Furthermore, the feasibility of the proposed scheme in the two-/three- Euclidean space is analyzed and demonstrated.

This letter considers the robust transceiver design for multiple-input multiple-output interference channels under channel state information mismatch. According to alternating schemes, an adaptive algorithm is proposed to solve the minimum SINR maximization problem. Simulation results show the convergence and the effectiveness of the proposed algorithm.

In this paper, a multi-data and multi-ACK verified selective forwarding attacks (SFAs) detection scheme is proposed for containing SFAs. In our scheme, each node (in addition to the nodes in the hotspots area) generates multiple acknowledgement (ACK) message for each received packet to confirm the normal packet transmission. In multiple ACK message, one ACK is returned along the data forwarding path, other ACKs are returned along different routing paths, and thus malicious nodes can be located accurately. At the same time, source node send multiple data routing, one is primary data routing, the others are backup data routing. Primary data is routed to sink directly, but backup data is routed to nodes far from sink, and then waits for the returned ACK of sink when primary data is routed to sink. If a node doesn't receive the ACK, the backup data is routed to sink, thus the success rate of data transmission and lifetime can be improved. For this case, the MDMA scheme has better potential to detect abnormal packet loss and identify suspect nodes as well as resilience against attack. Theoretical analysis and experiments show that MDMA scheme has better ability for ensuring success rate of data transmission, detecting SFA and identifying malicious nodes.

In this paper, we propose a new interference alignment (IA) scheme that jointly designs the linear transmitter and receiver for the 2-user MIMO X channel system, using minimum total mean square error criterion, subject to each transmitter power constraint. We show that transmitters and receivers under such criteria could be realized through a joint iterative algorithm. Considering the imperfection of channel state information (CSI), we also extend the minimum mean square error interference alignment schemes for the MIMO X channel with CSI estimation error. A robust iterative algorithm which is insensitve to CSI estimation error is proposed. Simulation results are also provided to demonstrate the proposed algorithm.

In this letter, a lattice-reduction-aided (LRA) minimum mean square error (MMSE) Tomlinson-Harashima precoding (THP) is proposed for multiple input multiple output (MIMO) systems. The extended channel is exploited to develop the LRA MMSE-THP based on the lattice reduction method. Simulation results show that the proposed scheme significantly outperforms the conventional MMSE THP and the LRA zero-forcing (ZF) THP and achieves full diversity order.

Compared with the unicast scenario, X channels with multicast messaging can support richer transmission scenarios. The transmission efficiency of the wireless multicast X channel is an important and open problem. This article studies the degrees of freedom of a propagation-delay based multicast X channel with two transmitters and arbitrary receivers, where each transmitter sends K different messages and each receiver desires K - 1 of them from each transmitter. The cyclic polynomial approach is adopted for modeling and analysis. The DoF upper bound is analyzed and shown to be unreachable. Then a suboptimal scheme with one extra time-slot cycle is proposed, which uses the cyclic interference alignment method and achieves a DoF of K - 1. Finally, the feasibility conditions in the Euclidean space are derived and the potential applications are demonstrated for underwater acoustic and terrestrial radio communications.

To obtain a full picture of potential applications for propagation-delay based X channels, it is important to obtain all feasible schemes of cyclic interference alignment including the encoder, channel instance, and decoder. However, when the dimension goes larger, theoretical analysis about this issue will become tedious and even impossible. In this letter, we propose a computer-aided solution by searching the channel space and the scheduling space, which can find all feasible schemes in details. Examples are given for some typical X channels. Computational complexity is further analyzed.

Underwater acoustic channels (UWA) are usually sparse, which can be exploited for adaptive equalization to improve the system performance. For the shallow UWA channels, based on the proportional minimum symbol error rate (PMSER) criterion, the adaptive equalization framework requires the sparsity selection. Since the sparsity of the L0 norm is stronger than that of the L1, we choose it to achieve better convergence. However, because the L0 norm leads to NP-hard problems, it is difficult to find an efficient solution. In order to solve this problem, we choose the Gaussian function to approximate the L0 norm. Simulation results show that the proposed scheme obtains better performance than the L1 based counterpart.

The existing literature focuses on the applications of fast filter bank due to its excellent frequency responses with low complexity. However, the topic is not addressed related to the general transfer function expressions of the corresponding subfilters for a specific channel. To do this, in this paper, general closed-form transfer function expressions for fast filter bank are derived. Firstly, the cascaded structure of fast filter bank is modelled by a binary tree, with which the index of the subfilter at each stage within the channel can be determined. Then the transfer functions for the two outputs of a subfilter are expressed in a unified form. Finally, the general closed-form transfer functions for the channel and its corresponding subfilters are obtained by variables replacement if the prototype lowpass filters for the stages are given. Analytical results and simulations verify the general expressions. With such closed-form expressions lend themselves easily to analysis and direct computation of the transfer functions and the frequency responses without the structure graph.

In software defined radio systems, a channelizer plays an important role in extracting the desired signals from a wideband signal. Compared to the conventional methods, the proposed scheme provides a solution to design a digital channelizer extracting the multiple subband signals at different center frequencies with low complexity. To do this, this paper formulates the problem as an optimization problem, which minimizes the required multiplications number subject to the constraints of the ripple in the passbands and the stopbands for single channel and combined multiple channels. In addition, a solution to solve the optimization problem is also presented and the corresponding structure is demonstrated. Simulation results show that the proposed scheme requires smaller number of the multiplications than other conventional methods. Moreover, unlike other methods, this structure can process signals with different bandwidths at different center frequencies simultaneously only by changing the status of the corresponding multiplexers without hardware reimplementation.

A new data-aided carrier frequency offset (CFO) estimation technique is presented for correlative coded OFDM systems in the presence of strong multipath. Different from traditional data-aided estimation techniques, the technique estimates CFO by detecting amplitude of pilots rather than their phase shift and removes effects on CFO estimation due to intercarrier interference by an iterative compensation method. A theoretical analysis of its performance has been derived and simulation results comparing the new technique with a traditional data-aided estimation technique are presented.