In this paper, we propose two secure multiuser multiple-input multiple-output (MIMO) transmission approaches based on interference alignment (IA) in the presence of an eavesdropper. To deal with the information leakage to the eavesdropper as well as the interference signals from undesired transmitters (Txs) at desired receivers (Rxs), our approaches aim to design the transmit precoding and receive subspace matrices to minimize both the total inter-main-link interference and the wiretapped signals (WSs). The first proposed IA scheme focuses on aligning the WSs into proper subspaces while the second one imposes a new structure on the precoding matrices to force the WSs to zero. In each proposed IA scheme, the precoding matrices and the receive subspaces at the legitimate users are alternatively selected to minimize the cost function of a convex optimization problem for every iteration. We provide the feasible conditions and the proofs of convergence for both IA approaches. The simulation results indicate that our two IA approaches outperform the conventional IA algorithm in terms of the average secrecy sum rate.

Periodic interference frequently affects the measurement of small signals and causes problems in clinical diagnostics. Adaptive filters can be used as potential tools for cancelling such interference. However, when the interference has a frequency fluctuation, the ideal adaptive-filter coefficients for cancelling the interference also fluctuate. When the adaptation property of the algorithm is slow compared with the frequency fluctuation, the interference-cancelling performance is degraded. However, if the adaptation is too quick, the performance is degraded owing to the target signal. To overcome this problem, we propose an adaptive filter that suppresses the fluctuation of the ideal coefficients by utilizing a $rac{pi}{2}$ phase-delay device. This method assumes a frequency response that characterizes the transmission path from the interference source to the main input signal to be sufficiently smooth. In the numerical examples, the proposed method exhibits good performance in the presence of a frequency fluctuation when the forgetting factor is large. Moreover, we show that the proposed method reduces the calculation cost.

Interference alignment (IA) is a promising technology for eliminating interferences while it still achieves the optimal capacity scaling. However, in practical systems, the IA feasibility limit and the heavy signaling overhead obstructs employing IA to large-scale networks. In order to jointly consider these issues, we propose the feedback overhead-aware IA clustering algorithm which comprises two parts: adaptive feedback resource assignment and dynamic IA clustering. Numerical results show that the proposed algorithm offers significant performance gains in comparison with conventional approaches.

In this paper, we study the degrees of freedom (DoF) of a multiple-input multiple-output (MIMO) multiway relay channel (mRC) with two relays, two clusters and K (K≥3) users per cluster. We consider a clustered full data exchange model, i.e., each user in a cluster sends a multicast (common) message to all other users in the same cluster and desires to acquire all messages from them. The DoF results of the mRC with the single relay have been reported. However, the DoF achievability of the mRC with multiple relays is still an open problem. Furthermore, we consider a more practical scenario where no channel state information at the transmitter (CSIT) is available to each user. We first give a DoF cut-set upper bound of the considered mRC. Then, we propose a distributed interference neutralization and retransmission scheme (DINR) to approach the DoF cut-set upper bound. In the absence of user cooperation, this method focuses on the beamforming matrix design at each relay. By investigating channel state information (CSI) acquisition, we show that the DINR scheme can be performed by distributed processing. Theoretical analyses and numerical simulations show that the DoF cut-set upper bound can be attained by the DINR scheme. It is shown that the DINR scheme can provide significant DoF gain over the conventional time division multiple access (TDMA) scheme. In addition, we show that the DINR scheme is superior to the existing single relay schemes for the considered mRC.

An interference-aware dynamic channel assignment scheme is proposed with consideration of co-tier interference for the downlink of an OFDMA/FDD based dense small-cell network. The proposed scheme adaptively assigns subchannels to the small-cell user equipment (SUE) according to the given traffic load and interference effect from neighbor small-cell access points. The simulation results show that the proposed scheme outperforms the other schemes based on the graph coloring algorithm in terms of the mean SUE capacity.

In this paper, the authors propose an integer linear programming (ILP) model for static multi-car elevator operation problems. Here, “static” means that all information which make the behavior of the elevator system indeterministic is known before scheduling. The proposed model is based on the trip-based ILP model for static single-car elevator operation problems. A trip of an elevator is a one-directional movement of that elevator, which is labaled upward or downward. In the trip-based ILP model, an elevator trajectory is scheduled according to decision variables which determine allocations of trips to users of an elevator system. That model has such an advantage that the difficulty in solving ILP formulations resulted by that model does not depend on the length of the planning horizon nor the height of the considered building, thus is effective when elevator trajectories are simple. Moreover, that model has many variables relevant to elevators' positions. The proposed model is resulted by adding 3 constraints which are basically based on those variables and make it possible to prevent elevators in a same shaft from interfering. The first constraint simply imposes the first and last floors of an upper trip to be above those of its lower trip. The second constraint imagines the crossing point between upper and lower trips and imposes it ahead of or behind the lower trip according to their directions. The last constraint estimates future positions of elevators and imposes the upper trip to be above floors of passengers on the lower trip. The basic validity of the proposed model is displayed by solving 90 problem instances and examining elevator trajectories generated from them, then comparing objective function values of elevator trajectories on a multi-car elevator system with those on single-car elevator systems.

The layered cell configuration, in which a large number of small cells are set in a macro-cell coverage area, is attracting much attention recently as a promising approach to handle the rapidly increasing mobile data traffic. In this configuration, cells of various sizes, from macro to small, are placed in various locations, so that the variation in the number and the distribution of the users among cells becomes much wider than in conventional macro-cell homogeneous networks. Therefore, even in the layered cell configuration, the users in the cell with many users and low received signal quality may experience low throughput especially at cell edge. This is because such users experience both low spectral efficiency and few radio resources. In order to resolve this issue, a lot of techniques have been proposed such as load balancing and cooperative multi-point transmission. In this paper, we focus on scheduling priority control as a simple solution that can also be used in combination with load balancing and coordinated multi-point transmission. We propose an adaptive scheduling priority control scheme based on the congestion and user distribution of each cell and clarify the effect of the proposed method by computer simulations.

In this paper, we investigate the problem of maximizing the weighted sum outage rate in multiuser multiple-input single-output (MISO) interference channels, where the transmitters have no knowledge of the exact values of channel coefficients, only the statistical information. Unfortunately, this problem is nonconvex and very difficult to deal with. We propose a new, provably convergent iterative algorithm where in each iteration, the original problem is approximated as second-order cone programming (SOCP) by introducing slack variables and using convex approximation. Simulation results show that the proposed SOCP algorithm converges in a few steps, and yields a better performance gain with a lower computational complexity than existing algorithms.

Multiple notch filters are used to suppress narrow-band or sinusoidal interferences in digital signals. In this paper, we propose a novel optimization design technique of an infinite impulse response (IIR) multiple notch filter. It is based on the Nelder-Mead simplex method. Firstly, the system function of the desired notch filter is constructed to form the objective function of the optimization technique. Secondly, the design parameters of the desired notch filter are optimized by Nelder-Mead simplex method. A weight function is also introduced to improve amplitude response of the notch filter. Thirdly, the convergence and amplitude response of the proposed technique are compared with other Nelder-Mead based design methods and the cascade-based design method. Finally, the practicability of the proposed notch filter design technique is demonstrated by some practical applications.

In multi user multiple input multiple output systems, spatial precoding is typically employed as an interference cancellation technique. This technique, however, requires accurate channel state information at the transmitter and limits the mobility of the mobile station (MS). Instead of spatial precoding, this letter implements collaborative interference cancellation (CIC) for interference suppression. In CIC, neighboring MSs share their received signals without decoding and equivalently increase the number of received antennas. The performance is evaluated through a field experiment using a vehicle that is equipped with seven MSs and moves around an urban area.

Non-orthogonal multiple access (NOMA) enables multiple mobile devices to share the same frequency band. In a conventional NOMA scheme, the receiver of a far user detects its desired signal without canceling the signal for a near user. However, the signal for the near user acts as interference and degrades the accuracy of likelihood values for the far user. In this paper, a joint maximum likelihood detection scheme for the far user of the NOMA downlink is proposed. The proposed scheme takes the interference signal into account in calculating the likelihood values. Numerical results obtained through computer simulation show that the proposed scheme improves the performance by from 0.2dB to 3.1dB for power allocation coefficients of 0.2 to 0.4 at a bit error rate (BER) of 10-2 relative to the conventional scheme.

In this paper, we investigate the degrees of freedom (DoF) of a MIMO cellular interfering network (CIN) with L (L≥3) cells and K users per cell. Previous works established the DoF upper bound of LK(M+N)/(LK+1) for the MIMO CIN by analyzing the interference alignment (IA) feasibility, where M and N denote the number of antennas at each base station (BS) and each user, respectively. However, there is still a gap between the DoF upper bound and the achievable DoF in existing designs. To address this problem, we propose two linear IA schemes without symbol extensions to jointly design transmit and receive beamforming matrices to align and eliminate interference. In the two schemes, the transmit beamforming vectors are allocated to different cluster structures so that the inter-cell interference (ICI) data streams from different ICI channels are aligned. The first scheme, named fixed cluster structure (FCS-IA) scheme, allocates ICI beamforming vectors to the cluster structures of fixed dimension and can achieve the DoF upper bound under some system configurations. The second scheme, named dynamic cluster structure IA (DCS-IA) scheme, allocates ICI beamforming vectors to the cluster structures of dynamic dimension and can get a tradeoff between the number of antennas at BSs and users so that ICI alignment can be applied under various system configurations. Through theoretical analysis and numerical simulations, we verify that the DoF upper bound can be achieved by using the FCS-IA scheme. Furthermore, we show that the proposed schemes can provide significant performance gain over the time division multiple access (TDMA) scheme in terms of DoF. From the perspective of DoF, it is shown that the proposed schemes are more effective than the conventional IA schemes for the MIMO CIN.

In a network with dense deployment of multiple-input multiple-output (MIMO) small cells, coverage overlap between the small cells produces intercell-interference, which degrades system capacity. This paper proposes an intercell-interference management (IIM) scheme that aims to maximize system capacity by using both power control for intercell-interference coordination (ICIC) on the transmitter side and interference cancellation (IC) on the receiver side. The power control determines transmit power levels at the base stations (BSs) by employing a neural network (NN) algorithm over the backhaul. To further improve the signal to interference plus noise ratio (SINR), every user terminal (UT) employs a multiuser detector (MUD) as IC. The MUD detects not only the desired signals, but also some interfering signals to be cancelled from received signals. The receiver structure consists of branch metric generators (BMGs) and MUD. BMGs suppress residual interference and noise in the received signals by whitening matched filters (WMFs), and then generate metrices by using the WMFs' outputs and symbol candidates that the MUD provides. On the basis of the metrices, the MUD detects both the selected interfering signals and the desired signals. In addition, the MUD determines which interfering signals are detected by an SINR based replica selection algorithm. Computer simulations demonstrate that the SINR based replica selection algorithm, which is combined with channel encoders and packet interleavers, can significantly improve the system bit error rate (BER) and that combining IC at the receiver with NN power control at the transmitter can considerably increase the system capacity. Furthermore, it is shown that choosing the detected interfering signals by the replica selection algorithm can obtain system capacity with comparable loss and less computational complexity compared to the conventional greedy algorithm.

Spatial stochastic models have been much used for performance analysis of wireless communication networks. This is due to the fact that the performance of wireless networks depends on the spatial configuration of wireless nodes and the irregularity of node locations in a real wireless network can be captured by a spatial point process. Most works on such spatial stochastic models of wireless networks have adopted homogeneous Poisson point processes as the models of wireless node locations. While this adoption makes the models analytically tractable, it assumes that the wireless nodes are located independently of each other and their spatial correlation is ignored. Recently, the authors have proposed to adopt the Ginibre point process — one of the determinantal point processes — as the deployment models of base stations (BSs) in cellular networks. The determinantal point processes constitute a class of repulsive point processes and have been attracting attention due to their mathematically interesting properties and efficient simulation methods. In this tutorial, we provide a brief guide to the Ginibre point process and its variant, α-Ginibre point process, as the models of BS deployments in cellular networks and show some existing results on the performance analysis of cellular network models with α-Ginibre deployed BSs. The authors hope the readers to use such point processes as a tool for analyzing various problems arising in future cellular networks.

The indexes of the degradation of C/N, ΔT/T and I/N, which can be converted from one to another, are used to evaluate the impact of interference on the satellite link. However, it is not suitable to intuitively understand how these parameters degrade the quality of services. In this paper, we propose to evaluate the impact of interference on the performance of BSS (Broadcasting Satellite Services) in terms of the increase rate of the outage time caused by the rain attenuation. Some calculation results are given for the 12GHz band BSS in Japan.

In this letter, we present a spectrally efficient multicast method which enables a transmitter to simultaneously transmit multiple multicast streams without any interference among multicast groups. By using unique combiners at receivers with multiple antennas within each multicast group, the proposed method simplifies multiple channels between the transmitter and the receivers to an equivalent channel. In addition, we establish the sufficient condition for the system configuration which should be satisfied for the channel simplification and provide a combiner design technique for the receivers. To remove interference among multicast groups, the precoder for the transmitter is designed by utilizing the equivalent channels. By exploiting time resources efficiently, the channel simplification (CS) based method achieves a higher sum rate than the time division multiplexing (TDM) based method, which the existing multicast techniques fundamentally employ, at high signal-to-noise ratio (SNR) regime. Furthermore, we present a multicast method combining the CS based method with the TDM based method to utilize the benefits of both methods. Simulation results successfully demonstrate that the combined multicast method obtains a better sum rate performance at overall SNR regime.

In this paper, we consider filter-and-forward relay beamforming using orthogonal frequency-division multiplexing (OFDM) in the presence of inter-block interference (IBI). We propose a filter design method based on a constrained max-min problem, which aims to suppress IBI and also avoid deep nulls in the frequency domain. It is shown that IBI can be suppressed completely owing to the employment of beamforming with multiple relays or multiple receive antennas at each relay when perfect channel state information (CSI) is available. In addition, we modify the proposed method to cover the case where only the partial CSI for relay-receiver channels is available. Numerical simulation results show that the proposed method significantly improves the performance as the number of relays and antennas increases due to spatial diversity, and the modified method can make use of the channel correlation to improve the performance.

Interference alignment (IA) is a method to improve the capacity of cell-edge users and thus attracts an intense research interest. We focus on the IA extended to the multiple-input multiple-output (MIMO) interference network. In this method, each coordinated transmitter generates beamforming vectors to align interference from different transmitters into confined subspace at each receiver. Then, using singular value decomposition (SVD) with the relative magnitude coefficients, transmitters calculate the beamforming vectors and the received vectors. However, in this method it is difficult to determine the value of the relative magnitude coefficients so that the system capacity is improved, because it is necessary to solve the non-linear function of multivariable. In this paper, we propose a design method of the relative magnitude coefficients of interference channels to improve system capacity using Brent's method on the K-User MIMO interference channel (MIMO-IFC). The proposed method can improve system capacity, though the system complexity increases due to Brent's method that requires multiple SVD calculation to calculate the null space. Thus, instead of using SVD, we introduce the complexity reduction method to calculate the null space of the matrix. Furthermore, we extend the proposed method to be applicable for more common systems where all base stations have the same number of transmit antennas. Through simulation, we show that the proposed method achieves a higher system capacity than the conventional one. We also show that the method that calculates the null space needs much lower complexity than SVD. In addition, we show that the proposed design method reduces the degradation of the system capacity caused by the interference not eliminated, and achieves the fairness of capacities among users for an increase of the number of design coefficients.

This paper presents an adaptive interference-aware receiver for multiuser multiple-input multiple-output (MU-MIMO) downlink systems in wireless local area network (WLAN) systems. The MU-MIMO downlink technique is one of the key techniques that are newly applied to WLAN systems in order to support a very high throughput. However, the simultaneous communication of several users causes inter-user interference (IUI), which adversely affects receivers. Therefore, in order to prevent IUI, a precoding technique is defined at the transmitter based on feedback from the receiver. Unfortunately, however, the receiver still suffers from interference, because the precoding technique is prone to practical errors from the feedback quantization and subcarrier grouping scheme. Whereas ordinary detection schemes are available to mitigate such interference, such schemes are unsuitable because of their low performance or high computational complexity. In this paper, we propose an switching algorithm based on the norm ratio between an effective channel matrix for the desired signal and that of the interfering signals. Simulation results based on the IEEE 802.11ac standard show that the proposed algorithm can achieve near-optimal performance with a 70% reduction in computational complexity.

This paper presents a 60 GHz analog/digital beamforming receiver that effectively suppresses interference signals, targeting the IEEE 802.11ad/WiGig standard. Combining two-stream analog frontends with interference rejection digital signal processing, the analog beamforming steers the antenna beam to the desired direction while the digital beamforming provides gain suppression in the interference direction. A prototype has been built with 40 nm CMOS analog frontends as well as offline baseband digital signal processing. Measurements show a 3.1 dB EVM advantage over conventional two-stream diversity during a packet collision situation.