This paper proposes a linear interference alignment (IA) scheme which can be used for uplink channels in a general multicell multiuser MIMO cellular network. The proposed scheme aims to align interference caused by signals from a set of transmitters into a subspace which is established by the signals from only a subset of those transmitters, thereby effectively reducing the number of interfering transmitters. The total degrees of freedom (DoF) achievable by the proposed scheme is given in closed-form expression, and a numerical analysis shows that the proposed scheme can achieve the optimal DoF in certain scenarios and provides a higher total DoF than other related schemes in most cases.
The IA scheme given in @cite_31 , which is called subspace IA, is the first IA scheme developed for cellular networks. The scheme exploits channel decomposibility to align interference into a subspace smaller than the desired signal space and can achieve high total DoF when the number of users is large and the number of cells is small. However, only uplink channels in single-antenna cellular networks were considered in @cite_31 , and the scheme can only be applied when the channel has the special property of decomposibility, which, for example, is not satisfied by channels with independent identically distributed coefficients @cite_37 .
@cite_31 @cite_37
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We develop an interference alignment (IA) technique for a downlink cellular system. In the uplink, IA schemes need channel-state-information exchange across base-stations of different cells, but our downlink IA technique requires feedback only within a cell. As a result, the proposed scheme can be implemented with a few changes to an existing cellular system where the feedback mechanism (within a cell) is already being considered for supporting multi-user MIMO. Not only is our proposed scheme implementable with little effort, it can in fact provide substantial gain especially when interference from a dominant interferer is significantly stronger than the remaining interference: it is shown that in the two-isolated cell layout, our scheme provides four-fold gain in throughput performance over a standard multi-user MIMO technique. We also show through simulations that our technique provides respectable gain under a more realistic scenario: it gives approximately 28 gain for a 19 hexagonal wrap-around-cell layout. Furthermore, we show that our scheme has the potential to provide substantial gain for macro-pico cellular networks where pico-users can be significantly interfered with by the nearby macro-BS. The feasibility condition of interference alignment (IA) for full-duplex (FD) multiple-input multiple-output (MIMO) cellular networks is considered. A necessary condition and a sufficient condition on the IA feasibility are established, characterizing the optimal sum degrees of freedom (DoF) for a broad class of network topologies. The necessary and sufficient condition is shown specially for a class of symmetric network topologies. The results demonstrate that FD operation at the base station with appropriate IA is able to improve the sum DoF than the conventional half-duplex operation. In this paper, we propose a new way of interference management for cellular networks. We develop the scheme that approaches to interference-free degree-of-freedom (dof) as the number K of users in each cell increases. Also we find the corresponding bandwidth scaling conditions for typical wireless channels: multi-path channels and single-path channels with propagation delay. The scheme is based on interference alignment. Especially for more-than-two-cell cases where there are multiple non-intended BSs, we propose a new version of interference alignment, namely subspace interference alignment. The idea is to align interferences into multi-dimensional subspace (instead of one dimension) for simultaneous alignments at multiple non-intended BSs. The proposed scheme requires finite dimensions growing linearly with K, i.e., O(K). For a three-cell constant cellular interfering network, a new property of alignment is identified, i.e., an interference alignment (IA) solution obtained in a user-cooperation scenario can also be applied to a non-cooperation environment. By using this property, an algorithm is proposed by jointly designing transmit and receive beamforming matrices. Analysis and simulation results show that more degrees of freedom (DoF) can be achieved compared with conventional schemes in most cases. In this paper, we propose jointly optimized linear transceiver algorithms called interference aware-coordinated beamforming (IA-CBF) for a two-cell system where each base station is equipped with multiple transmit antennas. To generalize IA-CBF to more than two-cell scenarios, a new beam-switching mechanism combined with IA-CBF is proposed. For a two-cell system, we derive a minimum-mean-square-error-type IA-CBF algorithm based on a lower bound on the achievable sum rate. We propose optimal (under an assumption of zero other-cell interference) and suboptimal transmit receive beamforming vectors through zero-forcing IA-CBF algorithms. We also investigate the optimality of the proposed IA-CBF algorithms with respect to the number of receive antennas. Numerical results confirm that the proposed system with two transmit receive antennas achieves the full degrees of freedom (a.k.a. multiplexing gain) of the two-cell multiple-input multiple-output channel while showing a better sum rate performance than competitive solutions such as non-cooperative eigen-beamforming and interference nulling. A three-dimensional ray tracing tool is also used to evaluate the proposed multi-cell IA-CBF algorithm. We explore the feasibility of linear interference alignment (IA) in MIMO cellular networks. Each base station (BTS) has N t transmit antennas, each mobile has N r receive antennas, and a BTS transmits a single beam to each active user. We present a necessary Zero-Forcing (ZF) condition for zero interference in terms of the number of users, the number of cells, N t and N r . We then examine the performance of iterative (forward-backward) algorithms for jointly optimizing the transmit precoders with linear receivers. Modifications of the max-SINR and minimum leakage algorithms are presented, which are observed to converge to a ZF solution whenever the necessary conditions are satisfied. In contrast, convergence of the (original) max-SINR algorithm is problematic when the necessary conditions are satisfied with (near) equality. A more restrictive ZF condition is presented, which predicts when these convergence problems are unlikely to occur. In a cooperative multiple-antenna downlink cellular network, maximization of a concave function of user rates is considered. A new linear precoding technique called soft interference nulling (SIN) is proposed, which performs at least as well as zero-forcing (ZF) beamforming. All base stations share channel state information, but each user's message is only routed to those that participate in the user's coordination cluster. SIN precoding is particularly useful when clusters of limited sizes overlap in the network, in which case traditional techniques such as dirty paper coding or ZF do not directly apply. The SIN precoder is computed by solving a sequence of convex optimization problems. SIN under partial network coordination can outperform ZF under full network coordination at moderate SNRs. Under overlapping coordination clusters, SIN precoding achieves considerably higher throughput compared to myopic ZF, especially when the clusters are large. This paper investigates the symmetric degrees of freedom (DoF) of MIMO cellular networks with G cells and K users per cell, having N antennas at each base station and M antennas at each user. In particular, we investigate achievability techniques based on either decomposition with asymptotic interference alignment (IA) or linear beamforming schemes, and show that there are distinct regimes of (G,K,M,N) where one outperforms the other. We first note that both one-sided and two-sided decomposition with asymptotic IA achieve the same degrees of freedom. We then establish specific antenna configurations under which the DoF achieved using decomposition based schemes is optimal by deriving a set of outer bounds on the symmetric DoF. For linear beamforming schemes, we first focus on small networks and propose a structured approach to linear beamforming based on a notion called packing ratios. Packing ratio describes the interference footprint or shadow cast by a set of transmit beamformers and enables us to identify the underlying structures for aligning interference. Such a structured beamforming design can be shown to achieve the optimal spatially normalized DoF (sDoF) of two-cell two-user cell network and the two-cell three-user cell network. For larger networks, we develop an unstructured approach to linear interference alignment, where transmit beamformers are designed to satisfy conditions for IA without explicitly identifying the underlying structures for IA. The main numerical insight of this paper is that such an approach appears to be capable of achieving the optimal sDoF for MIMO cellular networks in regimes where linear beamforming dominates asymptotic decomposition, and a significant portion of sDoF elsewhere. Remarkably, polynomial identity test appears to play a key role in identifying the boundary of the achievable sDoF region in the former case. In this paper, we propose a distributed multi-hop interference avoidance algorithm, namely, IAA to avoid co-channel interference inside a wireless body area network (WBAN). Our proposal adopts carrier sense multiple access with collision avoidance (CSMA CA) between sources and relays and a flexible time division multiple access (FTDMA) between relays and coordinator. The proposed scheme enables low interfering nodes to transmit their messages using base channel. Depending on suitable situations, high interfering nodes double their contention windows (CW) and probably use switched orthogonal channel. Simulation results show that proposed scheme has far better minimum SINR (12dB improvement) and longer energy lifetime than other schemes (power control and opportunistic relaying). Additionally, we validate our proposal in a theoretical analysis and also propose a probabilistic approach to prove the outage probability can be effectively reduced to the minimal. The Interfering Broadcast Channel (IBC) applies to the downlink of (cellular and or heterogeneous) multi-cell networks, which are limited by multi-user (MU) interference. The interference alignment (IA) concept has shown that interference does not need to be inevitable. In particular spatial IA in the MIMO IBC allows for low latency transmission. However, IA requires perfect and typically global Channel State Information at the Transmitter(s) (CSIT), whose acquisition does not scale well with network size. Also, the design of transmitters (Txs) and receivers (Rxs) is coupled and hence needs to be centralized (cloud) or duplicated (distributed approach). CSIT, which is crucial in MU systems, is always imperfect in practice. We consider the joint optimal exploitation of mean (channel estimates) and covariance Gaussian partial CSIT. Indeed, in a Massive MIMO (MaMIMO) setting (esp. when combined with mmWave) the channel covariances may exhibit low rank and zero-forcing might be possible by just exploiting the covariance subspaces. But the question is the optimization of beamformers for the expected weighted sum rate (EWSR) at finite SNR. We propose explicit beamforming solutions and indicate that existing large system analysis can be extended to handle optimized beamformers with the more general partial CSIT considered here. We study the degrees of freedom (DoF) of cellular networks in which a full duplex (FD) base station (BS) equipped with multiple transmit and receive antennas communicates with multiple mobile users. We consider two different scenarios. In the first scenario, we study the case when half duplex (HD) users, partitioned to either the uplink (UL) set or the downlink (DL) set, simultaneously communicate with the FD BS. In the second scenario, we study the case when FD users simultaneously communicate UL and DL data with the FD BS. For both network models, we completely characterize the sum DoFs by developing achievable schemes and obtaining matching upper bounds. The key idea of the proposed scheme is to carefully allocate UL and DL information streams using interference alignment and beamforming techniques. As a consequence of the result, we show that the DoF can approach the two-fold gain over the HD systems when the number of users becomes large enough as compared to the number of antennas at the BS. We propose joint spatial division and multiplexing (JSDM), an approach to multiuser MIMO downlink that exploits the structure of the correlation of the channel vectors in order to allow for a large number of antennas at the base station while requiring reduced-dimensional channel state information at the transmitter (CSIT). JSDM achieves significant savings both in the downlink training and in the CSIT uplink feedback, thus making the use of large antenna arrays at the base station potentially suitable also for frequency division duplexing (FDD) systems, for which uplink downlink channel reciprocity cannot be exploited. In the proposed scheme, the multiuser MIMO downlink precoder is obtained by concatenating a prebeamforming matrix, which depends only on the channel second-order statistics, with a classical multiuser precoder, based on the instantaneous knowledge of the resulting reduced dimensional “effective” channel matrix. We prove a simple condition under which JSDM incurs no loss of optimality with respect to the full CSIT case. For linear uniformly spaced arrays, we show that such condition is approached in the large number of antennas limit. For this case, we use Szego's asymptotic theory of Toeplitz matrices to show that a DFT-based prebeamforming matrix is near-optimal, requiring only coarse information about the users angles of arrival and angular spread. Finally, we extend these ideas to the case of a 2-D base station antenna array, with 3-D beamforming, including multiple beams in the elevation angle direction. We provide guidelines for the prebeamforming optimization and calculate the system spectral efficiency under proportional fairness and max-min fairness criteria, showing extremely attractive performance. Our numerical results are obtained via asymptotic random matrix theory, avoiding lengthy Monte Carlo simulations and providing accurate results for realistic (finite) number of antennas and users. A new scheme that allows cell gateways (base stations) to borrow channels from adjacent gateways in a cellular communication system is presented. Borrowed channels are used with reduced transmitted power to limit interference with cochannel cells. No channel locking is needed. The scheme, which can be used with various multiple access techniques, permits simple channel control management without requiring global information about channel usage throughout the system. It provides enhanced traffic performance in homogeneous environments and also can be used to relieve spatially localized traffic overloads (tele-traffic 'hot spots'). Co-channel interference analysis shows that the scheme can maintain the same SIR as nonborrowing schemes. Analytical models using multidimensional birth-death processes and decomposition methods are devised to characterize performance. The results which are also validated by simulation indicate that significantly increased traffic capacity can be achieved in comparison with nonborrowing schemes. > In this paper, we analyze the feasibility of linear interference alignment (IA) for multi-input-multi-output (MIMO) interference broadcast channel (MIMO-IBC) with constant coefficients. We pose and prove the necessary conditions of linear IA feasibility for general MIMO-IBC. Except for the proper condition, we find another necessary condition to ensure a kind of irreducible interference to be eliminated. We then prove the necessary and sufficient conditions for a special class of MIMO-IBC, where the numbers of antennas are divisible by the number of data streams per user. Since finding an invertible Jacobian matrix is crucial for the sufficiency proof, we first analyze the impact of sparse structure and repeated structure of the Jacobian matrix. Considering that for the MIMO-IBC the sub-matrices of the Jacobian matrix corresponding to the transmit and receive matrices have different repeated structure, we find an invertible Jacobian matrix by constructing the two sub-matrices separately. We show that for the MIMO-IBC where each user has one desired data stream, a proper system is feasible. For symmetric MIMO-IBC, we provide proper but infeasible region of antenna configurations by analyzing the difference between the necessary conditions and the sufficient conditions of linear IA feasibility. We show that the maximization of the sum degrees-of-freedom for the static flat-fading multiple-input multiple-output (MIMO) interference channel is equivalent to a rank constrained rank minimization problem (RCRM), when the signal spaces span all available dimensions. The rank minimization corresponds to maximizing interference alignment (IA) so that interference spans the lowest dimensional subspace possible. The rank constraints account for the useful signal spaces spanning all available spatial dimensions. That way, we reformulate all IA requirements to requirements involving ranks. Then, we present a convex relaxation of the RCRM problem inspired by recent results in compressed sensing and low-rank matrix completion theory that rely on approximating rank with the nuclear norm. We show that the convex envelope of the sum of ranks of the interference matrices is the normalized sum of their corresponding nuclear norms and introduce tractable constraints that are asymptotically equivalent to the rank constraints for the initial problem. We also show that our heuristic relaxation can be tuned for the multi-cell interference channel. Furthermore, we experimentally show that in many cases the proposed algorithm attains perfect interference alignment and in some cases outperforms previous approaches for finding precoding and zero-forcing matrices for interference alignment. Inter-cell interference coordination (ICIC) and intra-cell diversity (ICD) play important roles in improving cellular downlink coverage. By modeling cellular base stations (BSs) as a homogeneous Poisson point process (PPP), this paper provides explicit finite-integral expressions for the coverage probability with ICIC and ICD, taking into account the temporal spectral correlation of the signal and interference. In addition, we show that, in the high-reliability regime, where the user outage probability goes to zero, ICIC and ICD affect the network coverage in drastically different ways: ICD can provide order gain, whereas ICIC only offers linear gain. In the high-spectral efficiency regime where the SIR threshold goes to infinity, the order difference in the coverage probability does not exist; however, a linear difference makes ICIC a better scheme than ICD for realistic path loss exponents. Consequently, depending on the SIR requirements, different combinations of ICIC and ICD optimize the coverage probability. We propose an interference alignment scheme for the L cell multiuser interference channel, where M antennas are used at the base stations and N antennas are used at user terminals. To handle the large number of interference vectors from other cells, the proposed method aligns interference vectors such that they fall in a rank one vector space at the other cell base station receivers. After the alignment, we can achieve the sum DoF (K) values of, K=M when N <; 2(L-1), K=L(M-1) when N≥ (L-1)M. For other cases, we can achieve K=M-L+(L-1) [N L-1] in the L cell interference network, where [·] is the integer floor function. We investigate the open problem of characterizing the multiplexing gain offered by FD in a network of M cells (compared to the gain of two available on a single link). While self-interference cancellation is fundamental in realizing full duplex (FD) capability, the more challenging problem in a network-wide deployment of FD communication is a new form of uplink-downlink interference, namely UDI, caused by transmission of uplink clients on the downlink reception of other clients operating in the same frequency band during FD. We leverage spatial interference alignment (IA) as an effective approach to address UDI and characterize the scalability of the FD's multiplexing gain (in terms of M) by providing a closed-form expression. To the best of our knowledge, this is the first characterization of FD's multiplexing gain in a multi-cell network. We also provide an IA construction that can achieve the best scaling possible. Further, we extend our results to practical settings with limited number of clients and limited information sharing between access points. In this paper, a dynamic resource allocation scheme is proposed to avoid interference amongst coexisting Wireless Body Area Networks (WBAN). In the proposed scheme, each WBAN generates a table consisting of interfering nodes from coexisting WBANs in its vicinity. Then each WBAN broadcasts this table to its neighbors, which allows for efficient interpretation of an Interference Region (IR) between each pair of WBANs. The nodes in the IR are later allocated orthogonal sub-channels; whilst nodes that do not exist in the IR can potentially transmit in the same time interval. We further demonstrate a precise trade- off between the minimum interference level and spatial reuse. Simulation results show that our proposed scheme has far better spectral efficiency compared to the conventional orthogonal schemes, whilst maintaining an acceptable interference level. We also provide mathematical analysis on the proposed scheme to validate its efficiency for increasing spectral efficiency and avoiding interference. To further reduce the interference level, we propose a probabilistic approach, and analytically show that the outage probability can be effectively reduced at the cost of very small change in the spatial reuse factor. Index Terms—Wireless Body Area Networks, Spectral Effi- ciency, IEEE 802.15.6, Interference Mitigation We consider a cooperative wireless network in the presence of one or more eavesdroppers, and exploit node cooperation for achieving physical (PHY) layer based security. Two different cooperation schemes are considered. In the first scheme, cooperating nodes retransmit a weighted version of the source signal in a decode-and-forward (DF) fashion. In the second scheme, referred to as cooperative jamming (CJ), while the source is transmitting, cooperating nodes transmit weighted noise to confound the eavesdropper. We investigate two objectives: i) maximization of the achievable secrecy rate subject to a total power constraint and ii) minimization of the total power transmit power under a secrecy rate constraint. For the first design objective, we obtain the exact solution for the DF scheme for the case of a single or multiple eavasdroppers, while for the CJ scheme with a single eavesdropper we reduce the multivariate problem to a problem of one variable. For the second design objective, existing work introduces additional constraints in order to reduce the degree of difficulty, thus resulting in suboptimal solutions. Our work raises those constraints, and obtains either an analytical solution for the DF scheme with a single eavesdropper, or reduces the multivariate problem to a problem of one variable for the CJ scheme with a single eavesdropper. Numerical results are presented to illustrate the proposed results and compare them to existing work.