This letter considers the robust Tomlinson-Harashima Precoding(THP) transceiver design for Multiple-Input Multiple-Output (MIMO) interference channel (IC). Assuming bounded channel state information (CSI) error, we deal with the optimization for minimizing the worst case per-user mean square error (MSE) and sum MSE. We present an approximate approach to derive the upper bound of the constraint leading to less semidefinite. Then the alternate approach is adopted to update the receiver matrix by solving second-order-cone programming (SOCP), and update the transmitter matrix and feedback matrix by solving semidefinite program (SDP), respectively. Simulation results show that the proposed method achieves similar performance of the S-procedure method, whereas the computation complexity is reduced significantly, especially for the system with large number of transmit antennas.

X communication model with two receivers is introduced to underwater acoustic networks, in which each transmitter sends an independent message to each receiver. Based on distance aligned structure, we propose a scheme, which can perform perfect interference alignment. The feasibility is also illustrated in three dimensional Euclidean space.

A reduced complexity quantization error correction method for lattice reduction aided (LRA) vector precoding is proposed. For LRA vector precoding,Babai's approximation procedure can generate quantization errors leading to performance loss. Instead of making a list to correct all possible errors as is done in the existing scheme, we propose a novel method in which only a subset of all possible errors are corrected. The size of the subset is determined by the probability distribution of the number of actual errors. Thus, the computation complexity of our correction procedure is reduced with little performance loss compared with the existing correction scheme.

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.

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.

In this letter, non-orthogonal amplify-and-forward (NAF) is considered in a half-duplex two-way system. We derive the closed-form outage probability in the high signal-to-noise ratio (SNR) region, and approximate it with a simpler version to enable power allocation. Then a closed-form power allocation scheme is proposed to improve the outage performance; it uses only statistical channel knowledge (SCK). It is validated that our analyses agree with simulation results and the proposed power allocation approaches the optimal power allocation.

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.