In this letter, we study the capacity of fading channels with perfect channel side information (CSI) at the receiver and quantized CSI at the transmitter. We present a general algorithm for the joint design of optimal quantization and power control for maximizing the forward link capacity over flat fading channels. Numerical results for Rayleigh fading are given.

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.

Space-time coding (STC) schemes for communication systems employing multiple transmit and receive antennas have received considerable interest recently. On space-time coding, some algorithms with perfect channel state information (CSI) have been proposed. In certain fast varying situation, however, it may be difficult to estimate the channel accurately and it is natural to study the blind detection algorithm without CSI. In this paper, based on subspace, a new blind detection algorithm without CSI is proposed. Using singular value decomposition (SVD) on output signal, noise subspace and signal subspace, which keep orthogonal to each other, are obtained. By searching the intersection of the signal subspace and the limited symbol vector set, symbol detection is achieved. The simulations illustrate that the proposed algorithm significantly improves system performance by receiving more output signals relative to transmit symbols. Furthermore, the presented algorithm is robust to the fading channel that changes between two successive blocks.

For the frequency-division-duplex (FDD)-based massive multiple-input multiple-output (MIMO) systems, channel state information (CSI) feedback plays a critical role. Although deep learning has been used to compress the CSI feedback, some issues like truncation and noise still need further investigation. Facing these practical concerns, we propose an improved model (called CsiNet-Plus), which includes a truncation process and a channel noise process. Simulation results demonstrate that the CsiNet-Plus outperforms the existing CsiNet. The performance interchangeability between truncated decimal digits and the signal-to-noise-ratio helps support flexible configuration.

For the three-user X channel, its degree of freedom (DoF) 9/5 has been shown achievable theoretically through asymptotic model with infinite resources, which is impractical. In this article, we explore the propagation delay (PD) feature among different links to maximize the achievable DoF with the minimum cost. Since perfect interference alignment (IA) is impossible for 9 messages within 5 time-slots, at least one extra time-slot should be utilized. By the cyclic polynomial approach, we propose a scheme with the maximum achievable DoF of 5/3 for 10 messages within 6 time-slots. Feasibility conditions in the Euclidean space are also deduced, which demonstrates a quite wide range of node arrangements.

For the performance deficiency of the pilot symbol aided channel estimation in orthogonal frequency division multiplexing (OFDM) systems, the wavelets network interpolation channel estimator is proposed. By contrast with conventional methods, wavelets network interpolation channel estimator can guarantee the high transmission rate and lower Bit error rates (BER). Computer simulation results demonstrate that the proposed channel estimation method exhibit an improved performance compared to the conventional linear channel estimation methods and is robust to fading rate, especially in fast fading channels.

In Video-on-Demand (VoD) services, the playback continuity is one of the most crucial factors for end-user to judge service quality. It is even more significant than the actual video image quality since new generation VoD users commonly have heterogeneous requirements on service according to their context. Moreover, managing dynamic situations in VoD service is always a challenge, especially in the unpredictable user preferences and network conditions. In this paper, i) Autonomous Decentralized VoD System (ADVODS) has been proposed to satisfy different service quality demands of users and, ii) the Autonomous Node Allocation Technology (ANAT) is proposed for assuring service continuity. With the help of autonomous nodes and mobile agents, ANAT can applies different backup policies to users with different Service Level Agreements (SLA), and dynamically update the backup schema to adapt the changing situations such as various service time or congestion events. Drawing on the evaluation results this paper shows that proposed system architecture has a better performance on streaming service provision and continuity.

A novel blind channel estimation scheme is proposed for OFDM systems employing PSK modulation. This scheme minimizes the number of possible channels by exploiting the constant modulus property, chooses a best fit over the possible channels by exploiting the finite alphabet property of information signals, and achieves competitive performance with low computational complexity. Results comparing the new scheme with the finite-alphabet based channel estimation are presented.

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.

This letter solves the energy efficiency optimization problem for the simultaneous wireless information and power transfer (SWIPT) systems with non-orthogonal multiple access (NOMA), multiple input single output (MISO) and power-splitting structures, where each user may have different individual quality of service (QoS) requirements about information and energy. Nonlinear energy harvesting model is used. Alternate optimization approach is adopted to find the solution, which shows a fast convergence behavior. Simulation results show the proposed scheme has higher energy efficiency than existing dual-layer iteration and throughput maximization methods.

In this paper a new adaptive multi-input multi-output (MIMO) channel estimation and multiuser detection algorithm based kernel space iterative inversion is proposed. The functions of output signals are mapped from a low dimensional space to a high dimensional reproducing kernel Hilbert space. The function of the output signals is represented as a linear combination of a set of basis functions, and a Mercer kernel function is constructed by the distribution function. In order to avoid finding the function f(.) and g(.), the correlation among the output signals is calculated in the low dimension space by the kernel. Moreover, considering the practical application, the algorithm is extended to online iteration of mixture system. The computer simulation results illustrated that the new algorithm increase the performance of channel estimation, the global convergence, and the system stability.