Secure degrees of freedom for general MIMO interference channel under rank-deficiency

As a more trackable performance metric for secrecy capacity,the secure degrees of freedom(SDoF)are widely studied for most multiuser networks in the high signal to noise ratio(SNR)region.However,the SDoF for these networks under rank-deficiency and arbitrary antenna configurations have not yet been determined.In this paper,the SDoF of two-user general multiple-input multiple-output(MIMO)interference channel with confidential messages(ICCM)under rank-deficiency are derived.For the two-user rank-deficient MIMO ICCM,the model is generalized to fully asymmetric settings,where the transmitters and receivers are equipped with arbitrary antennas.The outer bound of SDoF is the union of three outer bounds that are based on the Fano’s inequality and the secrecy constraints,the secrecy penalty lemma and the role of a helper lemma,and the transmitters cooperation,respectively.The SDoF region is subdivided into five regions according to the number of transceivers antennas,and each region has an achievability scheme with designed null space transmission and alignment techniques.Numerical results indicate that the SDoF increase at first and then decrease as the rank of the channel matrix decreases.The SDoF improve by increasing the transmitting antenna or reducing receiving antenna,but the effect of the transmitting antenna is greater.

Low complexity robust linear transceiver design for MIMO interference channel

This paper focuses on the linear transceiver design for multiple input multiple output（MIMO） interference channel（IC）, in which a bounded channel error model is assumed. Two optimization problems are formulated as minimizing maximum per-user mean square error（MSE） and sum MSE with the per-transmitter power constraint. Since these optimization problems are not jointly convex on their variable matrices, the transmitter and receiver can be optimized alternately respectively. For each matrix, an approximated approach is presented where the upper bound of constraint is derived so that it has less semidefinite, thus the problem can be viewed as second-order-cone programming（SOCP） and gets less computational complexity. Compared with the conventional S-procedure method, the proposed approach achieves similar performance, but reduces the complexity significantly, especially for the system with large scale number of antennas.

Method of interference cancellation based on space-time code in MIMO interference channels

The authors in this article investigated how to cancel multi-user interference with low feedback amount over 3-user multiple input multiple output （MIMO） interference channel using space-time code and precoders. Space-time block code with coding rate 2 was designed, also zero vectors were introduced into each codeword. The multi-user interference is mitigated by pre-coding at the transmitters and nonlinear operation and unidirectional cooperation link at the receivers. Compared with the existing scheme for the same scene, the proposed scheme greatly reduces feedback amount and improves the sum degrees of freedom （DOF）. Simulation demonstrates the validity of the proposed scheme.

Spectrum Efficiency Maximization for Cooperative Power Beacon-Enabled Wireless Powered Communication Networks

We consider a spectrum efficiency(SE)maximization problem for cooperative power beacon-enabled wireless powered communication networks(CPB-WPCNs),where each transmitter harvests en-ergy from multi-antenna power beacons(PBs)and transmits data to the corresponding receiver.For data transmission,both orthogonal transmission,i.e.,the time splitting(TS)mode,and non-orthogonal trans-mission,i.e.,the interference channel(IC)mode,are considered.Aiming to improve the system SE,the energy beamformers of PBs,the transmit power,and the transmit time duration of transmitters are jointly optimized.For the TS mode,the original non-convex problem is transformed into a convex opti-mization problem by means of variable substitution and semidefinite relaxation(SDR).The rank-one na-ture of this SDR is proved,and then a Lagrange-dual based fast algorithm is proposed to obtain the opti-mal solution with much lower complexity.For the IC mode,to conquer the strong non-convexity of the problem,a branch-reduce-and-bound(BRB)mono-tonic optimization algorithm is designed as a bench-mark.Furthermore,a low-complexity distributed suc-cessive convex approximation(SCA)algorithm is pre-sented.Finally,simulation results validate the perfor-mance of the proposed algorithms,achieving optimal-ity within only 1%∼2%computation time compared to the CVX solver in the TS mode and achieving 98%of the optimal performance in the IC mode.

Ergodic interference alignment for MIMO interference system with variable channel

The authors pay focus on the K user multiple-input multiple-output（MIMO） Gaussian interference channel（IC） with M transmitting antennas and N receiving antennas, in which min（M, N）/max（M, N）≧（K-1）/[K（K-2）] and K 〉3. The channel coefficients are variable, time varying or frequency selectively drawn from a continuous distribution. Based on ergodic interference alignment（IA）, an achievable scheme was proposed to achieve a total of KMN/（M ＋N） degrees of freedom（DoF）. The ergodic IA scheme can reach the optimal Do F value with simply linear beamforming and finite symbols. Furthermore, the achievable rate of the ergodic IA scheme was derived at any signal-to-noise ratio（SNR）. With numerical simulation, the performance of the proposed scheme is evaluated.

Distributed Multi-Cell Multi-User MISO Downlink Beamforming via Deep Reinforcement Learning

The sum rate maximization beamforming problem for a multi-cell multi-user multiple-input single-output interference channel(MISO-IC)system is considered.Conventionally,the centralized and distributed beamforming solutions to the MISO-IC system have high computational complexity and bear a heavy burden of channel state information exchange between base stations(BSs),which becomes even much worse in a large-scale antenna system.To address this,we propose a distributed deep reinforcement learning(DRL)based approach with lim⁃ited information exchange.Specifically,the original beamforming problem is decomposed of the problems of beam direction design and power allocation and the costs of information exchange between BSs are significantly reduced.In particular,each BS is provided with an inde⁃pendent deep deterministic policy gradient network that can learn to choose the beam direction scheme and simultaneously allocate power to users.Simulation results illustrate that the proposed DRL-based approach has comparable sum rate performance with much less information exchange over the conventional distributed beamforming solutions.

Performance Analysis and Simulation of Higher Order Modulations for Ka-Band Fixed Satellite Communication

The performance analysis and simulation of spectrally efficient modulation schemes , MPSK and MQAM, for Ka-band fixed satellite communication system are provided. The effects of bandwidth limitation, nonlinearityity distortion and adjacent channel interference (ACI) in Ka-band satellite channel corrupted by additive white Gaussian noise (AWGN) are taken into account. The analytical expressions of the HER of coherent MPSK and MQAM signal are obtained and shown to be in good agreement with the simulation results.

GSM Co-Channel and Adjacent Channel Interference Analysis and Optimization

Most current Global System for Mobile Communications （GSM） frequency planning methods evaluate the interference and assign frequencies based on measurement reports. Assigning the same or adjacent frequencies to cells close to each other will introduce co-channel and adjacent channel interference which will reduce network performance. Traditionally, man power is used to check and allocate new frequencies which is time consuming and the accuracy is not satisfactory. This paper presents an intelligent analysis method for optimization of co-channel and adjacent channel interference by exploiting cell configuration information. The method defines an interference evaluation model by analyzing various factors such as the base station layer, the azimuth ward relationship, and the cell neighborhood relationships. The interference for each frequency is evaluated and the problem frequencies are optimized. This method is verified by a large number of actual datasets from an in-service GSM network. The results show this method has better intelligence, accuracy, timeliness, and visualization than traditional methods.

Hybrid scheme for three-cell multi-user MIMO cellular networks

Orthogonal schemes are usually adopted for cell-edge users in a cellular network, where the spectrum is poorly utilized. A new interference alignment （IA） based space-division hybrid （IA-SDH） scheme is proposed by joint design transmit precoding matrices and beamforming matrices for a three-cell constant cellular network, where users at cell-center work with a conventional scheme while users at cell-edge utilize an IA scheme. Therefore, the cell-edge users suffer no interference and cell-center users are only affected by negligible inter-cell interference. Analysis simulation shows that more users can be served simultaneously than that of a conventional scheme in certain user distributions.