Efficient Subchannel Allocation Based on Clustered Interference Alignment in Ultra-Dense Femtocell Networks

In this paper, we exploit clustered interference alignment(IA) for efficient subchannel allocation in ultra-dense orthogonal frequency division multiplexing access(OFDMA) based femtocell networks, which notably improves the spectral efficiency as well as addresses the feasibility issue of IA. Our problem is formulated as a combinatorial optimization problem which is NP-hard. To avoid obtaining its optimal solution by exhaustive search, we propose a two-phases efficient solution with low-complexity. The first phase groups all the femtocell user equipments(FUEs) into disjoint clusters, and the second phase allocates subchannels to the formed clusters where IA is performed. By doing this, the intra-cluster and inter-cluster interferences are mitigated by clustered IA and subchannel allocation in ultra-dense femtocell networks, respectively.Also, low-complexity algorithm is proposed to solve the corresponding sub-problem in each phase. Simulation results demonstrate that the proposed scheme not only outperforms other related schemes, but also provides a close performance to the optimal solution.

Rayleigh Quotient Based Interference Alignment Spectrum Sharing in MIMO Cognitive Radio Networks

An interference alignment(IA)spectrum sharing method based on Rayleigh quotient is proposed for distributed multi-user multi-antenna cognitive radio(CR) networks.The interference from cognitive users(CUs)to the primary(PR) system is constrained through the Rayleigh quotients of channel matrices to deal with the absence of PR users(PUs) in the IA process.As a result,the IA scheme can be applied in CR networks without harmful interference to PUs.Compared with existing IA based spectrum sharing methods,the proposed method is more general because of breaking the restriction that CUs can only transmit on the idle sub-channels of the PR system.Moreover,in comparison to other four spectrum sharing methods applicable in general scene,the proposed method leads to improved performance of achievable sum rate of the CR system as well as guarantees the transmission of PUs.

Interference Alignment Based on Subspace Tracking in MIMO Cognitive Networks with Multiple Primary Users

The interference alignment （IA） algorithm based on FDPM subspace tracking （FDPM-ST IA） is proposed for MIMO cognitive network （CRN） with multiple primary users in this paper. The feasibility conditions of FDPM-ST IA is also got. Futherly, IA scheme of secondary network and IA scheme of primary network are given respectively without assuming a priori knowledge of interference covariance matrices. Moreover, the paper analyses the computational complexity of FDPM-ST IA. Simulation results and theoretical calculations show that the proposed algorithm can achieve higher sum rate with lower computational complexity.

Admission control based on beamforming and interference alignment for D2D communication underlaying cellular networks

An admission control algorithm based on beamforming and interference alignment for device-to-device( D2D) communication underlaying cellular networks is proposed. First, some portion of D2D pairs that are the farthest away from the base station( BS) is selected to perform joint zero-forcing beamforming together with the cellular user equipments( UEs) and is admitted to the cellular network. The interference of the BS transmitting signal to the cellular UEs and the portion of D2D pair is eliminated completely at the same time. Secondly,based on the idea of interference alignment,the definition of channel parallelism is given. The channel parallelism of the remaining D2D pairs which are not involved in joint zero-forcing beamforming is computed by using the channel state information from the BS to the D2D devices. The higher the channel parallelism,the less interference the D2D pair suffers from the BS. Finally,in a descending order of channel parallelism,the remaining D2D pairs are reviewed in succession to determine admission to the cellular network. The algorithm stops when the admission of a D2D pair decreases the system sum rate. Simulation results show that the proposed algorithm can effectively reduce the interference of the BS transmitting signal for D2D pairs and significantly improve system capacity. Furthermore, D2D communication is more applicable to short-range links.

Interference Alignment in Two-Way Relay Networks via Rank Constraints Rank Minimization

Interference alignment(IA) is one of the promising measures for the multi-user network to manage interference. The rank constraints rank minimization means that interference spans the lowest dimensional subspace and the useful signal spans all available spatial dimensions. In order to improve the performance of two-way relay network, we can use rank constrained rank minimization(RCRM) to solve the IA problem. This paper proposes left reweighted nuclear norm minimization-γalgorithm and selective coupling reweighted nuclear norm minimization algorithm to implement interference alignment in two-way relay networks. The left reweighted nuclear norm minimization-γ algorithm is based on reweighted nuclear norm minimization algorithm and has a novel γ choosing rule. The selective coupling reweighted nuclear norm minimization algorithm weighting methods choose according to singular value of interference matrixes. Simulation results show that the proposed algorithms considerably improve the sum rate performance and achieve the higher average achievable multiplexing gain in two-way relay interference networks.

The Average Achievable Rate of Multi-Antenna Two-Way Relay Networks with Interference Alignment

The large system analysis(LSA)has recently been shown to be a very useful tool for computing the average achievable rate.In this paper,we use LSA to derive the users’average achievable rate of multi-antenna two-way relay networks with interference alignment(IA),and we then derive the rate expressions under both equal power allocation and optimal power allocation.It is shown that the obtained closed-form rate expressions are functions of the average signal-to-noise ratio(SNR)for each data stream.Extensive simulation studies show that the average achievable rate expressions derived through LSA provide accurate estimates of the average achievable rate for two-way relay networks with interference alignment.

Achievement of Interference Alignment in General Underlay Cognitive Radio Networks: Scenario Classification and Adaptive Spectrum Sharing

Interference alignment(IA) is suitable for cognitive radio networks(CRNs).However, in IA spectrum sharing(SS) process of general underlay CRNs, transmit power of cognitive radio transmitters usually should be reduced to satisfy interference constraint of primary user(PU), which may lead to low signalto-noise-ratio at cognitive radio receivers(CRRs). Consequently, sum rate of cognitive users(CUs) may fall short of the theoretical maximum through IA. To solve this problem,we propose an adaptive IA SS method for general distributed multi-user multi-antenna CRNs. The relationship between interference and noise power at each CRR is analyzed according to channel state information, interference requirement of PU, and power budget of CUs. Based on the analysis, scenarios of the CRN are classified into 4 cases, and corresponding IA SS algorithms are properly designed. Transmit power adjustment, CU access control and adjusted spatial projection are used to realize IA among CUs. Compared with existing methods, the proposed method is more general because of breaking the restriction that CUs can only transmit on the idle sub-channels. Moreover, in comparison to other five IA SS methods applicable in general CRN, the proposed method leads to improved achievable sum rate of CUs while guarantees transmission of PU.

Interference Alignment Algorithm for Considering the Throughput of Cognitive Users in Cognitive MIMO Network

The cognitive multiple input multiple output( MIMO)network can utilize radio spectrum efficiently and satisfy the demand of high data rate. In order to decrease the interference during transmission,a new interference alignment( IA) algorithm based on cognitive MIMO networks is proposed in this paper. The algorithm is realized by designing two-level pre-coding, the first-level precoding aligns the interference generated by the cognitive users( CUs) to unused sub-channels of the primary user( PU),thereby eliminating the interference of CUs to PU; the second-level precoding is used to improve the throughput of CUs. Simulation shows that the proposed IA algorithm can eliminate the interference that the CUs produce on the PU and improve the throughput of CUs spontaneously.

On Multi-Frequency Channel Interference Alignment of 3 Channels and 4 Users

This paper explores the multi-frequency independent channel interference alignment(MFC-IA) system of 3 channels and4 users,and single data stream transmit,i.e.(3×3,1)~4 system.We derive the analytic solution for(3×3,1)~4 MFC-IA system.Based on the analytic solution,an optimization problem is proposed aim at the optimal IA solution.Then based on such a math model,we propose a simulated annealing(SA) algorithm to search optimal IA solution.The simulation results show that the simulated annealing IA algorithm has a better sum rate performance than iterative maximize signal to interference plus noise ratio(Max-SINR) algorithm.This result can be extended to single data stream multi-antenna IA system with 3 antennas and4 users.

Combination of interference alignment and beamforming in cellular networks

In this paper, we propose two joint transmit-receive iterative algorithms without the cooperation between different base stations based on the idea of interference alignment (IA) to improve the throughput of relay backhaul links in cellular networks for the case of imperfect channel knowledge,which can be implemented with small changes to existing TD-LTE standards. Unlike the previous interference alignment algorithms' only reducing the sum interference to the other receivers at the transmitter or the sum received Multi-user interference (MUI) at the receiver, our algorithm shapes the transmission of each data stream at transmitters in order not only to minimize interference to the other users, but also to minimize the interference between different streams objected to the same user, suppressing the MUI and Multi-stream interference (MSI) at receivers. The proposed algorithm I is to maximize the SINR at receivers. But the complexity is relatively high. Algorithm II only needs linear operations and sacrifices a little performance for much lower complexity compared to the Maximize SINR iterative algorithm which needs the inversion operation of matrix. It is also proved that the algorithm converges monotonically. The simulation results show that the techniques have considerable performance gain compared with the previous algorithms. Further research about power allocation is also discussed.

Coverage probability of cellular networks using interference alignment under imperfect CSI

Interference alignment （IA） is well understood to approach the capacity of interference channels, and believed to be crucial in cellular networks in which the ability to control and exploit interference is key. However, the achievable performance of IA in cellular networks depends on the quality of channel state information （CSI） and how effective IA is in practical settings is not known. This paper studies the use of IA to mitigate inter-cell interference of cellular networks under imperfect CSI conditions. Our analysis is based on stochastic geometry where the structure of the base station （BS） locations is considered by a Poisson point process （PPP）. Our main contribution is the coverage probability of the network and simulation results confirm the accuracy.

Closed-form interference alignment with heterogeneous degrees of freedom

Interference alignment(IA) has been recognized as a promising technique for obtaining the optimal degrees of freedom(DOF) in interference networks.A closed-form interference alignment design is proposed for three-cell uplink transmissions with heterogeneous DOFs.By exploiting the heterogeneity of DOFs from different transmission links,full or partial interference alignment precoders are calculated at each base station(BS).Aided by information exchange among BSs,the precoders can be finally obtained for all transmission links.Comparing to existing IA methods,the proposed scheme has a closed-form expression.Furthermore,there is no need to go through the iterative adaptation or jointly calculate the precoder and the equalizer.Simulation results show that the proposed design is able to achieve the optimal DOF performance with the advantage of perfect alignment capabilities.

Joint alignment and steering to manage interference

In wireless communication networks,mobile users in overlapping areas may experience severe interference,therefore,designing effective Interference Management(IM)methods is crucial to improving network performance.However,when managing multiple disturbances from the same source,it may not be feasible to use existing IM methods such as Interference Alignment(IA)and Interference Steering(IS)exclusively.It is because with IA,the aligned interference becomes indistinguishable at its desired Receiver(Rx)under the cost constraint of Degrees-of-Freedom(DoF),while with IS,more transmit power will be consumed in the direct and repeated application of IS to each interference.To remedy these deficiencies,Interference Alignment Steering(IAS)is proposed by incorporating IA and IS and exploiting their advantages in IM.With IAS,the interfering Transmitter(Tx)first aligns one interference incurred by the transmission of one data stream to a one-dimensional subspace orthogonal to the desired transmission at the interfered Rx,and then the remaining interferences are treated as a whole and steered to the same subspace as the aligned interference.Moreover,two improved versions of IAS,i.e.,IAS with Full Adjustment at the Interfering Tx(IAS-FAIT)and Interference Steering and Alignment(ISA),are presented.The former considers the influence of IA on the interfering user-pair's performance.The orthogonality between the desired signals at the interfered Rx can be maintained by adjusting the spatial characteristics of all interferences and the aligned interference components,thus ensuring the Spectral Efficiency(SE)of the interfering communication pairs.Under ISA,the power cost for IS at the interfered Tx is minimized,hence improving SE performance of the interfered communication-pairs.Since the proposed methods are realized at the interfering and interfered Txs cooperatively,the expenses of IM are shared by both communication-pairs.Our in-depth simulation results show that joint use of IA and IS can effectively manage multiple disturbances from the same source and improve the system's SE.

Successive Interference Cancellation and Alignment in K-User MIMO Interference Channels with Partial Unidirectional Strong Interference

Recently cellular networks have been densely and heterogeneously deployed indoors and outdoors to expand the network capacity,and thus the in-building propagation loss and the transmit power diversity of access points will exacerbate link heterogeneity and result in partial unidirectional strong interference.To make full use of the strong interference feature,we propose the successive interference cancellation and alignment(SICA)scheme in the K-user interference channel with partial unidirectional strong interference.SICA is designed to transmit two kinds of data streams simultaneously,the alignment streams and superposition streams.The alignment streams will follow the interference alignment criterion to maintain the optimal degrees of freedom(DoF)performance;the superposition streams are handled via successive interference cancellation at all the strongly interfered receivers to improve the overall achievable rate.The joint transceiver designs for SICA is modeled as a weighted sum rate(WSR)maximization problem,and then can be alternately solved for a local optimum according to the optimality equivalence between WSR and its corresponding weighted mean square error(WMMSE)problem.Simulation results have confirmed the sum rate improvement and DoF optimality of the proposed SICA scheme.

Interference alignment scheme for massive MIMO system

The performance of massive multiple-input multiple-output （MIMO） system is limited by pilot contamination. To reduce the pilot contamination, uplink and downlink precoding algorithms are put forward based on interference alignment criterion. In the uplink receiving processing, the target function aligns the pilot contamination and the interference signals to the same null space and acquires the maximal space degree of the desired signals. The uplink receiving precoding matrix is solved on maximal signal to interference plus noise ratio （SINR） criterion considering the impact of the pilot contamination on channel estimations. The uplink receiving precoding matrix is used as the downlink transmitting precoding matrix. Exploiting the channel reciprocity, it is proved that, if the uplink receiving precoding matrix achieves maximal S1NR, the identical precoding matrix can be used in the downlink transmission and acquires maximal signal to leakage plus noise ratio （SLNR）. Simulations show that the spectrum efficiency of the proposed algorithm can reach about 1.5 times higher than that of popular matched filtering （MF） precoding algorithm, and about 1.1 times higher than multi-cell minimum mean square error （MMSE） precoding algorithm. The performance of the proposed algorithm can be improved approximately linearly with the increasing of the number of antennas.

Nash bargaining solution based multi-cell and multi-user interference alignment scheme for cellular networks

In wireless cellular networks, the interference alignment （IA） is a promising technique for interference management. A new IA scheme for downlink cellular network with multi-cell and multi-user was proposed, in the proposed scheme, the interference in the networks is divided into inter-cell interference （ICI） among cells and inter-user interference （IUI） in each cell. The ICI is aligned onto a multi-dimensional subspace by multiplying the ICI alignment precoding matrix which is designed by the singular value decomposition （SVD） scheme at the base station （BS） side. The aligned ICI is eliminated by timing the interference suppression matrix which is designed by zero-forcing （ZF） scheme at the user equipment （UE） side. Meanwhile, the IUI is aligned by multiplying the IUI alignment precoding matrix which is designed based on Nash bargaining solution （NBS） in game theory. The NBS is solved by the particle swarm optimization （PSO） method. Simulations show that, compared with the traditional ZF IA scheme, the proposed scheme can obtain higher data rate and guarantee the data rate fairness of UEs with little additional complexity.

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.

Interference Suppression for MIMO Device to Device Pairs Underlaying Cellular Network

Device to device(D2D) communications may generate interference to the existing cellular networks.An interference suppression(IS) scheme is proposed in this paper.With this scheme,the threshold of D2D-pairs(D2D-Ps) communication was designed to reject the D2D-Ps which were not satisfied the threshold constraint,ensuring that the cellular users(CUs) had priority to use the spectrum resources.Then the interference from D2D-Ps at the receiver of CUs was eliminated first by precoding at the D2D transmitter and decoding at the CU's receiver.Next,the interference between D2D-Ps was suppressed by using interference alignment(IA).Performance analysis shows that the priority of CUs using the spectrum resources has been guaranteed;the interference generated on the cellular links is well eliminated;the interference between D2D-Ps can also be suppressed.

Interference-aware uplink transmission schemes for multicell MIMO system

In this paper we consider interference-aware uplink transmission schemes for multicell multiple-input multiple-output （MIMO） system. Unlike conventional transmission schemes without considering the interference probably caused to other cell, we jointly optimize the transceiver beamforming vectors to maximize the desired signals while removing the intercell interference. Specifically, for a two-cell system where each transmitter is equipped with two antennas, we derive the closed-form expression for the transmit scheme called coordinated beamforming （CBF） via generalized-eigen analysis. Moreover, when asymmetric interference is considered, we give a balancing beamforming （BBF） scheme where the interfering transmitter is to strike a compromise between maximizing the desired signal and minimizing the generated interference. Simulation results show that both schemes perform better than conventional schemes under different scenarios.