Proposed Interference Alignment Scheme Research Articles

Interference Alignment Using Reaction in Molecular Interference Channels.

Co-channel interference (CCI) is a performance limiting factor in molecular communication (MC) systems with shared medium. Interference alignment (IA) is a promising scheme to mitigate CCI in traditional communication systems. Due to the signal-dependent noise in MC systems, the traditional IA schemes are less useful in MC systems. In this paper, we propose a novel IA scheme in molecular interference channels (IFCs), based on the choice of releasing/sampling times. To cancel the aligned interference signals and reduce the signal dependent noise, we use molecular reaction in the proposed IA scheme. We obtain the feasible region for the releasing/sampling times in the proposed scheme. Further, we investigate the error performance of the proposed scheme. Our results show that the proposed IA scheme using reaction improves the performance significantly.

An interference alignment scheme based on limited feedback with differentiation in heterogeneous networks

AbstractThe traditional limited feedback scheme can use imperfect channel state information to achieve interference alignment (IA) in a fully connected situation. But these solutions could no longer be used directly in heterogeneous networks where partial connectivity is considered. To solve this problem, this article proposes an IA scheme based on limited feedback with differentiation for the two‐tiered heterogeneous network. First, users who are affected by different types and numbers of interference and corresponding base stations are divided into different units according to the partial connectivity of heterogeneous networks. Then, we design interference alignment algorithm for each unit separately. Next, considering the imperfect channel state information, we derive the leakage of interference caused by the limited feedback, and give expressions for the upper bound of sum rate loss in various units. Finally, dynamic feedback bit allocation is carried out to each unit with the goal of minimizing the throughput loss in the limited feedback system. The simulation results show that the proposed IA scheme can eliminate interference well and efficiency of limited feedback can be improved through dynamic feedback bit allocation, so that system can obtain higher sum rate than other schemes.

Optimal IA design and performance analysis for MIMO–OFDM systems with imperfect CSI

Both multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) are key technologies for the fifth-generation mobile communication systems. However, interference is one of the critical challenges in MIMO–OFDM systems that degrades the overall performance. In this study, a novel interference alignment (IA) design-based diagonal-block channel charter to mitigate the interference for MIMO–OFDM systems is proposed. The proposed IA scheme can be used in physical layer security, e.g. anti-location. Based on the diagonal-block charter of the channel matrix, the optimal degree of freedom, i.e. the maximum number of multiple data streams concurrently transmitted interference-free can be achieved by IA. Correspondingly, the authors present the closed-form IA design scheme for some special scenarios, and two iterative IA ones for general scenarios in detail. Furthermore, the performance analysis of IA systems with diagonal-block channel error is provided, where the imperfect channel state information case is considered. The simulation results show that the IA design based on the diagonal-block channel can improve the sum-rate performance effectively, by sufficiently exploiting the spatial and frequency resources.

Precoder Feedback Schemes for Robust Interference Alignment With Bounded CSI Uncertainty

This article presents limited feedback-based precoder quantization schemes for Interference Alignment (IA) with bounded channel state information (CSI) uncertainty. Initially, this work generalizes the min-max mean squared error (MSE) framework, followed by the development of robust precoder and decoder designs based on worst case MSE minimization. The proposed precoder and decoder designs capture the effect of CSI uncertainty using a single parameter, which is independent of the CSI uncertainty in the direct links. The IA algorithms derived employing these proposed designs are shown to be globally convergent under certain conditions. Moreover, precoder quantization schemes are presented for scenarios with and without CSI uncertainty for practical implementation of these techniques in systems with limited feedback. An optimal bit allocation scheme is presented to maximize the sum rate via analysis of the rate loss upper bound. Simulation results demonstrate the improved performance of the proposed IA schemes for various scenarios considering imperfect CSI as well as limited feedback.

Achievable Degrees of Freedom of Relay-Aided MIMO Cellular Networks Using Opposite Directional Interference Alignment

In this paper, we propose an interference alignment (IA) scheme for the multiple-input multiple-output (MIMO) uplink cellular network with the help of a relay which operates in half-duplex mode. The proposed scheme only requires global channel state information (CSI) knowledge at the relay, with no transmitter beamforming and time extension at the user equipment (UE), which differs from conventional IA schemes for cellular networks. We derive the feasibility condition of the proposed scheme for the general cellular network configuration and analyze the degrees-of-freedom (DoF) performance of the proposed IA scheme while providing a closed-form beamformer design at the relay. Extensions of the proposed scheme to downlink and full-duplex cellular networks are also proposed in this paper. The DoF performance of the proposed scheme is compared to those of linear IA scheme and relay-aided interference management scheme for a cellular network with no time extension. It is also shown that advantages similar to those in the uplink case can be obtained for the downlink case through the duality of a relay-aided interfering multiple-access channel (IMAC) and an interfering broadcast channel (IBC). Furthermore, the proposed scheme for a full-duplex cellular network is shown to have advantages identical to those of a number of proposed half-duplex cellular cases.

Interference Alignment Algorithm Based on Feedback Concentration in D2D Communications

This paper proposed an effective interference alignment algorithm based on channel state feedback concentration (FCIA) for device-to-device (D2D) communications. The algorithm iteratively calculates the precoding matrix by using the global channel state information. Furthermore, as D2D discovery is the premise of the D2D communications, an effective interference alignment algorithm based on D2D discovery is also proposed. Simulation results show that, the proposed FCIA algorithm reduces the feedback overhead for transmission coordination compared with the existing full feedback based algorithm. The proposed interference alignment scheme based on D2D discovery feedback is compared with the existing D2D discovery scheme: it is found that although the discovery time slots has increased by about 6.2%, the sum rate achieved by interference alignment is improved by almost 50%.

Parametrization and Applications of Precoding Reuse and Downlink Interference Alignment

In this paper, we consider the downlink communication of an arbitrary number of transmitters over broadcast interference channels. In order to suppress interference, we investigate a network-level linear precoding scheme dubbed precoding reuse. Such a technique is leveraged on the interference alignment (IA) principle, where the undesired signals overlap in a reduced-dimension subspace at the receivers. Precoding reuse relies on two cascaded precoders to suppress intra- and inter-cell interference and requires feedback only within a cell. We designed precoding reuse schemes for which interference suppression can be attained in a coordinated or uncoordinated fashion over a fixed number of quasi-static channel uses. We provide expressions for the parametrization of the precoders and investigate the advantages, limitations, suitable scenarios, and applications of the proposed IA scheme. Finally, we pointed out the open problems, where the proposed IA scheme and parametrization can be implemented with little effort, demanding minimum changes to an existing cellular system supporting multi-user MIMO.

Interference Alignment in Two-Tier Randomly Distributed Heterogeneous Wireless Networks Using Stochastic Geometry Approach

With the massive increase in wireless data traffic in recent years, multi-tier wireless networks have been deployed to provide much higher capacities and coverage. However, heterogeneity of wireless networks bring new challenges for interference analysis and coordination due to spatial randomly distributed transmitters. In this paper, we present a distance-dependent interference alignment (IA) approach for a generic two-tier heterogeneous wireless network, where transmitters in the first and second tiers are distributed as poisson point process (PPP) and poisson cluster process, respectively. The feasibility condition of the IA approach is used to find upper bound of the number of interference streams that can be aligned. The proposed IA scheme maximizes the second-tier throughput by using the tradeoff between signal-to-interference ratio and multiplexing gain. It is shown that acquiring accurate knowledge of the distance between the receiver in the second-tier and the nearest cross-tier transmitter only brings insignificant throughput gain compared with statistical knowledge of distance. Furthermore, the remaining cross-tier and intercluster interferences are modeled and analyzed using stochastic geometry technique. Numerical results validate the derived expressions of success probabilities and throughput, and show that the distance-dependent IA scheme significantly outperforms the traditional IA scheme in the presence of path-loss effect.

Interference Alignment for Partially Connected Downlink MIMO Heterogeneous Networks

In this paper, we propose interference alignment (IA) schemes for downlink multiple-input-multiple-output heterogeneous networks (HetNets) with partial connectivity, which is induced by the path loss and the low transmission power of small cells. Specifically, we consider two partially connected scenarios of HetNets. In the first scenario, we focus on the partial connectivity among small cells, whereas in the second scenario, we further consider the partial connectivity between the macrocell and small cells. For the first scenario, we first propose a two-stage IA scheme by exploiting the heterogeneity and partial connectivity of HetNets. Then, the influence of the number of served macro users on system degrees of freedom (DoFs) is investigated. In particular, we derive the condition under which serving one macro user achieves more DoFs than serving multiple macro users and design an algorithm to find the optimal number of served macro users to maximize the system DoFs. Afterward, we study the second scenario and extend the two-stage IA to this scenario. The simulation results show that the proposed IA schemes can significantly improve the system sum rate. Moreover, by considering the partial connectivity between the macro cell and small cells, the system performance can be further improved.

EIV-Based Interference Alignment Scheme with CSI Uncertainties

A novel interference alignment (IA) scheme based on the errors-in-variables (EIV) mathematic model has been proposed to overcome the channel state information (CSI) estimation error for the MIMO interference channels. By solving an equivalently unconstrained optimization problem, the proposed IA scheme employing a weighted total least squares (WTLS) algorithm can obtain the solution to a constrained optimization problem for transmit precoding (TPC) matrices and minimizes the distortion caused by imperfect CSI according to the EIV model. It is shown that the design of TPC matrices can be realized through an efficient iterative algorithm. The convergence of the proposed scheme is presented as well. Simulation results show that the proposed IA scheme is robust over MIMO interference channels with imperfect CSI, which yields significantly better sum rate performance than the existing IA schemes such as distributed iterative IA, maximum signal-to-interference-plus-noise ratio (Max SINR), and minimum mean square error (MMSE) schemes.

Interference alignment with delayed channel state information and dynamic AR-model channel prediction in wireless networks

Interference alignment (IA) is a promising technique that can effectively eliminate the interferences in multiuser wireless networks. However, it requires highly accurate channel state information (CSI) of the whole network at all the transmitters and receivers. In practical wireless systems, it is difficult to obtain the perfect knowledge of a dynamic channel. Particularly, the CSI at transmitters used in IA is usually delayed through feedback, which will dramatically affect the performance of IA. In this paper, the performance of IA with delayed CSI is studied. The expressions of the average signal to interference plus noise ratio and sum rate of IA networks with delayed CSI are established. To alleviate the influence of delayed CSI, an IA scheme based on dynamic autoregressive (AR)-model channel prediction is proposed, in which the parameters of AR mode are updated frequently. The CSI of the next time instant is predicted using the present and past CSI in the proposed scheme to improve the performance of IA networks. Two key factors of the scheme, window length and refresh rate are analyzed in detail. Simulation results are presented to show that the proposed IA scheme based on channel prediction can significantly improve its performance with delayed CSI.

New interference alignment schemes with full and half‐duplex relays for the quasi‐static X channel

In this study, two relay-aided interference alignment (IA) schemes are proposed for the quasi-static M × 2 X channel where M is the number of transmitters and two is the number of receivers, respectively. The first scheme utilises one full-duplex relay and the second one utilises two half-duplex relays. In the proposed schemes, the transmitters transmit signals in every time slot and the relays operate in the amplify-and-forward (AF) mode. By verifying the linear independence between the desired signals and the interference, it is shown that the proposed schemes can achieve 2M/(M + 1) degrees of freedom (DoF) which is the maximum DoF for the M × 2 X channel. It is also shown by using the concept of reciprocity that the proposed IA schemes are applicable to the 2 × M X channel. Finally, through the numerical analysis, it is confirmed that the proposed IA schemes provide good alternatives to the previously known relay-aided IA scheme.

On the Degrees of Freedom of Interference Alignment for Multicell MIMO Interfering Broadcast Channels

The interference alignment (IA) is a promising technique to efficiently mitigate interference and to enhance capacity of a wireless network. This paper proposes an interference alignment scheme for a cellular network with L cells and K users under a multiple-input multiple-output (MIMO) Gaussian interfering broadcast channel (IFBC) scenario. The proposed IA scheme aligns intercell interferences (ICI) into a small dimensional subspace through a cooperative receive beamforming and cancels both the ICI and interuser interferences (IUI) simultaneously through a transmit beamforming. We characterize the feasibility condition for the proposed IA to achieve a total number of degrees of freedom (DoF) of LK in terms of the numbers of transmit antennas and receive antennas. Then we derive the maximum number of DoF achieved by the proposed IA by finding an optimal dimension of ICI alignment subspace for a given antenna configuration. The numerical results show that the proposed IA scheme has a better DoF performance than the conventional schemes.

Interference alignment in K ‐user multiple‐input–multiple‐output interference channels with partially coordinated receivers

In a K-user multiple-input multiple-output (MIMO) interference channel where each N-antenna transmitter communicates with its corresponding M-antenna receiver by using d degrees of freedom (DoF), the feasibility condition for conventional interference alignment (IA) implies that M + N > d(K + 1). In this paper, we consider a K-user MIMO interference channel where averagely half of the total decoded data can be shared by receive nodes via partial coordination. We propose IA algorithms such that first, their feasibility condition can now be expressed as M + N > d(K + 4)/2, which further implies less number of antennas is needed in comparison with conventional IA techniques to achieve the same number of DoF; and second, even with this reduced number of antennas, their throughput is still comparable to that of conventional IA methods. This is particularly pronounced for asymptotically large K where the required number of antennas for the proposed IA schemes can be half of that of conventional IA techniques to secure the same number of DoF. Moreover, we also examine the performance of the proposed IA algorithms in the presence of both error propagations and channel estimation errors. Simulation results show that in these cases, the throughput of the proposed algorithms can be comparable to that of conventional IA techniques.

CSI Feedback Reduction for MIMO Interference Alignment

Interference alignment (IA) is a linear precoding strategy that can achieve optimal capacity scaling at high SNR in interference networks. Most of the existing IA designs require full channel state information (CSI) at the transmitters, which induces a huge CSI signaling cost. Hence it is desirable to improve the feedback efficiency for IA and in this paper, we propose a novel IA scheme with a significantly reduced CSI feedback. To quantify the CSI feedback cost, we introduce a novel metric, namely the feedback dimension. This metric serves as a first-order measurement of CSI feedback overhead. Due to the partial CSI feedback constraint, conventional IA schemes can not be applied and hence, we develop a novel IA precoder/decorrelator design and establish new IA feasibility conditions. Via dynamic feedback profile design, the proposed IA scheme can also achieve a flexible tradeoff between the degree of freedom (DoF) requirements for data streams, the antenna resources and the CSI feedback cost. We show by analysis and simulations that the proposed scheme achieves substantial reductions of CSI feedback overhead under the same DoF requirement in MIMO interference networks.

제한된 궤환 채널 기반 상향링크 MIMO/FDD 시스템에서의 효율적인 간섭 정렬 기법

Assuming perfect channel state information (CSI), the conventional interference alignment (IA) algorithm in the uplink cellular system suppresses inter-cell interference (ICI) by aligning ICI to a randomly selected reference vector. However, IA in practice relies on limited feedback between base stations and users, resulting in residual ICI. In this paper, we propose the optimization of the reference vector that minimizes the upper-bound of residual ICI power. Secondly, the iterative IA that designs the direction of transmit and receive filter is proposed to minimize the residual ICI as well as maximize the desired signals. Moreover, we propose the user scheduling method combined with proposed IA schemes which provides the multiuser diversity gain in multi-cell environments. Finally, the performance gain of the proposed IA algorithms compared with the existing IA are analyzed and demonstrated by simulation results.

Joint Design of Precoder and Power Allocation for Downlink Multi-Cell Multi-User Wireless Systems with Interference Alignment

In the paper, we propose a joint design of precoder and power allocation for downlink multi-cell multi-user wireless systems with interference alignment (IA). This non-iterative method is decomposed into two separate steps. First, we design the precoding and decoding matrices using IA, fully eliminating the interference between the effective channels. Then, on the basis of the pre-canceling, each base station performs equal power allocation among different users and adopts a joint optimization of precoding matrix and power allocation to maximize the information rate of the corresponding noninterfering effective channel. Meanwhile, we present the corresponding detection method for each noninterfering effective channel. It is analytically shown that the proposed IA scheme exploits less antenna resources than the search IA scheme does to achieve the same degrees of freedom. Moreover, the simulation results demonstrate that the proposed IA scheme shows better performance than the original IA scheme.