Interference Alignment Methods Research Articles

Selective interference alignment and neutralization in coordinated multipoint using multiuser MIMO

SummaryIn wireless communication, the concept of coordinated multipoint (CoMP) transmission is more attractive, and it transpired the notion based on interference management techniques. Interference alignment (IA) and interference neutralization (IN) methods can substantially align and neutralize the interference signals. The existing work in the CoMP transmission using multiuser multi‐input and multi‐output (MU‐MIMO) had long‐held problems such as specific limit of intercell (ICI) and cochannel interference (CCI) cancelation that contain low performance in cell‐edge users. The proposed framework of the transmission signal in selective interference alignment and neutralization (SIAN) CoMP MU‐MIMO system transmits multiple data streams in multipath by using downlink coordination between base stations and receiver side. This work contributes the individual perspectives to implement the IA and IN to align and cancel the interfered signals at the receiver side. Once the perspectives mentioned above are executed, zero‐forcing (ZF) and rechanneling filter are applied on the receiver side to eliminate residual ICI. In addition, spectral efficiency significantly improves the achievable data rate and enhances the performance of cell‐edge users and reduces the CCI at the receiver side. Furthermore, the antenna configuration signals are decoded to get the exact version of interference‐free signals with null path loss of signal transmission. The effectiveness of the proposed framework analyzes and verifies the numerical evaluation of the achievable degree of freedom. Finally, the simulation demonstrates the comparison of the proposed CoMP scheme with MIMO ZF and non‐CoMP schemes, which significantly improve the performance of spectral efficiency for cell‐edge users.

Mutual interference alignment for co-existing radar and communication systems

In this paper, we propose a mutual interference alignment (IA) method for interference elimination in co-existing multiple-input multiple-output (MIMO) radar and multi-user MIMO communication systems, namely, radar-communication systems. Traditional IA methods proposed for communication systems cannot be directly adopted in the radar-communications due to failure to fulfill the requirements of radar target detection. In contrast, our proposed mutual IA method can efficiently improve the signal-to-noise ratio (SNR) needed by radar functionalities without reducing the degrees-of-freedom (DoFs) of communication system, which implies no degradation for the communication performance. The algorithm idea is first to align all interferences at every receiver to one signal space, then the interferences can be easily canceled by receive filter. It is examined by the Neyman-Pearson (NP) test for radar functionality, while the communication performance is evaluated by DoFs and bit error rate (BER) analysis. Both theory analysis and numerical results are provided to validate the effectiveness of the proposed mutual IA method for co-existing radar and communication systems.

Degrees of Freedom for Half-Duplex and Full-Duplex Multi-User Cognitive Radios

The degrees of freedom (DoF) of multi-user cognitive radios (CR) under half-duplex (HD) and full-duplex (FD) are studied in this work. Due to the fact that FD adopted multiple cognitive users (CUs) suffer not only self-interference (SI) and primary-user interference (PUI) but also multi-user interference (MUI) from the other CUs, the DoF metric is constrained by various interference factors and shows scale invariance properties with respect to the temporal, frequency and spatial dimensions. In this regard, the average DoF is characterized in both spatio and temporal dimensions using limitation calculation (LC) and interference alignment (IA) methods, under interweave, underlay, overlay and hybrid CR patterns. Due to the multi-user specified impacts, the achievable DoF of CU is constrained by the maximum transmit power of the other CUs, and the HD and FD tradeoff for multi-user CR is determined by both MUI and time-antenna splitting. Theoretical analysis indicates that the secondary user power and secondary user number only inflict impacts on LC and IA based average DoF respectively. Moreover, because of distributed CR processing, the average DoF for MU CR is upper-bounded by that of single-user CR. Simulation results validate the effects of MUI, SI, PUI and user number on the average DoF. It shows that IA achieves higher DoF than that of LC for multi-user CR, indicating that the DoF loss due to MUI can be reduced if interference mitigation is available.

Interference Alignment for One-Hop and Two-Hops MIMO Systems With Uncoordinated Interference

Providing higher data rate is a momentous goal for wireless communications systems, while interference is an important obstacle to reach this purpose. To cope with this problem, interference alignment (IA) has been proposed. In this paper, we propose two rank minimization methods to enhance the performance of IA in the presence of uncoordinated interference, i.e. , interference that cannot be properly aligned with the rest of the network and thus is a crucial issue. In this scenario, perfect and imperfect channel state information (CSI) cases are considered. Our proposed approaches employ the $l_{2}$ and the Schatten- $p$ norms to approximate the rank function, due to its non-convexity. Also, we propose a new convex relaxation to expand the feasible set of our optimization problem, providing lower rank solutions compared to other IA methods from the literature. In addition, we propose a modified weighted-sum method to deal with interference in the relay-aided MIMO interference channel, which employs a set of weighting parameters in order to find more solutions.

Ergodic Interference Alignment for Spectrum Sharing Radar-Communication Systems

In this paper, we propose an ergodic interference alignment (IA) method for interference elimination in spectrum sharing multiple-input multiple-output (MIMO) radar and multi-user MIMO communication systems. In existing ergodic IA methods, the channel state information (CSI) is generally assumed to be constant, but time-varying channels should be considered in practice. Differently, our proposed ergodic IA allows to time-varying and/or frequency selective channels for spectrum sharing radar-communication systems. The essence is equivalent to design a simple transmit beamforming, which helps to find a pair of desired complementary channels easily without long-time system delay, therefore, the interferences can be effectively cancelled. The proposed method is evaluated by generalized likelihood ratio test (GLRT) and signal to interference plus noise ratio (SINR) for the radar functionality, while the communication functionality is examined by bit error rate (BER) performance. Both theoretical analysis and simulation results validate that the effectiveness of the ergodic IA method for spectrum sharing radar-communication systems.

An Iterative Interference Alignment Algorithm for the General MIMO X Channel

Interference alignment (IA) has been shown as an important technique to achieve a linear capacity scaling in wireless communications. However, the IA scheme over finite signaling dimensions for a general multiple-input-multiple-output (MIMO) X channel is still rarely studied. The main challenge of MIMO X channels is that the two sets of conditions for IA, namely the interference nulling conditions and the rank preservation conditions, get coupled. The usual IA methods for the interference channel and the broadcasting channel cannot be applied anymore. In this paper, we show that the rank preservation conditions can be replaced by a group of specific rank conditions, under which the IA problem is simplified. Then, based on this technique, an iterative algorithm of IA is designed for the MIMO X channel. The algorithm is designed with limited signaling dimensions. From the simulation results, we find that the algorithm has good performances even under limited signal-to-noise ratio.

Joint IA and SFBC Macrocells and Small-Cells Coexistence under Minor Information Exchange

The deployment of small-cells within the boundaries of a macrocell is considered to be an effective solution to cope with the current trend of higher data rates and improved system capacity. In the current heterogeneous configuration with the mass deployment of small-cells, it is preferred that these two cell types will coexist over the same spectrum, because acquiring additional spectrum licenses for small-cells is difficult and expensive. However, the coexistence leads to cross-tier/intersystem interference. In this context, this contribution investigates interference alignment (IA) methods in order to mitigate the interference of macrocell base station towards the small-cell user terminals. More specifically, we design a diversity-oriented interference alignment scheme with space-frequency block codes (SFBCs). The main motivation for joint interference alignment with SFBC is to allow the coexistence of two systems under minor intersystem information exchange. The small-cells just need to know what space-frequency block code is used by the macrocell system and no intersystem channels need to be exchanged, contrarily to other schemes recently proposed. Numerical results show that the proposed method achieves a performance close to the case where full cooperation between the tiers is allowed.

Transmission Cooperative Strategies for MIMO-OFDM Heterogeneous Networks

Mobile traffic in cellular networks is increasing exponentially, mainly due to the use of data intensive ser- vices like video. One way to cope with these demands is to reduce the cell-size by deploying small-cells along the coverage area of the current macro-cell system. The de- ployment of small-cells significantly improves indoor cov- erage. Nevertheless, as additional spectrum licenses are difficult and expensive to acquire it is expected that the macro and small-cells will coexist under the same spec- trum. The coexistence of the two systems results in cross- tier/inter-system interference. In this context, we design several interference alignment based techniques for the downlink of heterogeneous networks, in order to cancel the interference generated from macro-cell at small-cell user terminals. More specifically, in this contribution we design interference alignment methods under different levels of inter-system coordination and the constraint that the per- formance of macro-cell system is kept close to the case where small-cell system is switched-off. Numerical results demonstrate that the proposed methods achieve close to the optimal performance with low overhead.

Semi-Blind Interference Alignment Techniques for Small Cell Networks

This paper investigates the application of blind and semi-blind interference alignment methods in clustered small cell networks. First, we examine two simple straightforward extensions of blind interference alignment and observe that neither of them is uniformly superior under all user distribution. Then, we exploit the location information of the users and base stations (BSs) in the cluster to define the semi-blind interference alignment problem, whose objective function is to minimize the supersymbol length by grouping the users that can be served in the same time slot. We show that this problem is NP-hard and propose two heuristic centralized algorithms that can provide effective solutions. The first scheme, top-level semi-blind supersymbol design, employs a grouping indicator matrix to determine the supersymbol while the second scheme, ordered semi-blind supersymbol design, constructs the supersymbol in an ordered and greedy fashion. Finally, we propose a more decentralized scheme which does not have the location information of all users and BSs in the cluster, but the BS utilizes the long-term SINR values, obtained via feedback, of each user it serves. By numerical simulations, we show that the proposed semi-blind algorithms perform uniformly better than pure blind interference alignment schemes for any possible user distribution scenario.

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.