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.
For general multicell multiuser uplink channels, @cite_24 proposed a new scheme called unstructured IA scheme which appeared to provide a high DoF performance, but for a given uplink channel the feasibility of the scheme cannot be determined until the scheme is actually applied and checked by a numerical test. On the other hand, the IA scheme in @cite_2 aimed to align ICI into a one-dimensional subspace, and because this IA constraint was too stringent to be satisfied, only a fraction of the ICI could be aligned. This problem was then resolved in @cite_19 by consolidating ICI into a multi-dimensional subspace rather than a one-dimensional subspace. By extending the scheme in @cite_16 , which was designed only for three-cell multiuser uplink channels, the scheme in @cite_10 can be applied to a general uplink channel; however, its DoF performance decreases when the size of the uplink channel increases as the scheme can only suppress the interference caused by one interfering user regardless of the size of the uplink channel.
@cite_24 @cite_19 @cite_2 @cite_16 @cite_10
2951830991 2126019998 2117196063 2016172526
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. 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). We consider a power control scheme for maximizing the information capacity of the uplink in single-cell multiuser communications with frequency-flat fading, under the assumption that the users attenuations are measured perfectly. Its main characteristics are that only one user transmits over the entire bandwidth at any particular time instant and that the users are allocated more power when their channels are good, and less when they are bad. Moreover, these features are independent of the statistics of the fading. Numerical results are presented for the case of single-path Rayleigh fading. We show that an increase in capacity over a perfectly-power controlled (Gaussian) channel can be achieved, especially if the number of users is large. By examining the bit error-rate with antipodal signalling, we show the inherent diversity in multiuser communications over fading channels. This paper considers the optimal uplink transmission strategy that achieves the sum-capacity in a multiuser multi-antenna wireless system. Assuming an independent identically distributed block-fading model with transmitter channel side information, beamforming for each remote user is shown to be necessary for achieving sum-capacity when there is a large number of users in the system. This result stands even in the case where each user is equipped with a large number of transmit antennas, and it can be readily extended to channels with intersymbol interference if an orthogonal frequency division multiplexing modulation is assumed. This result is obtained by deriving a rank bound on the transmit covariance matrices, and it suggests that all users should cooperate by each user using only a small portion of available dimensions. Based on the result, a suboptimal transmit scheme is proposed for the situation where only partial channel side information is available at each transmitter. Simulations show that the suboptimal scheme is not only able to achieve a sum rate very close to the capacity, but also insensitive to channel estimation error. 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. Massive MIMO is a variant of multiuser MIMO where the number of base-station antennas M is very large (typically ≈ 100), and generally much larger than the number of spatially multiplexed data streams (typically ≈ 10). The benefits of such approach have been intensively investigated in the past few years, and all-digital experimental implementations have also been demonstrated. Unfortunately, the front-end A D conversion necessary to drive hundreds of antennas, with a signal bandwidth of the order of 10 to 100 MHz, requires very large sampling bitrate and power consumption. In order to reduce such implementation requirements, Hybrid Digital-Analog architectures have been proposed. In particular, our work in this paper is motivated by one of such schemes named Joint Spatial Division and Multiplexing (JSDM), where the downlink precoder (resp., uplink linear receiver) is split into the product of a baseband linear projection (digital) and an RF reconfigurable beamforming network (analog), such that only a reduced number m M of A D converters and RF modulation demodulation chains is needed. In JSDM, users are grouped according to similarity of their channel dominant subspaces, and these groups are separated by the analog beamforming stage, where multiplexing gain in each group is achieved using the digital precoder. Therefore, it is apparent that extracting the channel subspace information of the M -dim channel vectors from snapshots of m-dim projections, with m M , plays a fundamental role in JSDM implementation. In this paper, we develop novel efficient algorithms that require sampling only m = O(2 √ M) specific array elements according to a coprime sampling scheme, and for a given p M , return a p-dim beamformer that has a performance comparable with the best p-dim beamformer that can be designed from the full knowledge of the exact channel covariance matrix. We assess the performance of our proposed estimators both analytically and empirically via numerical simulations. We also demonstrate by simulation that the proposed subspace estimation methods provide near-ideal performance for a massive MIMO JSDM system, by comparing with the case where the user channel covariances are perfectly known. 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. We show that the 3 user M_T x M_R MIMO interference channel has d(M,N)=min(M (2-1 k),N (2+1 k)) degrees of freedom (DoF) normalized by time, frequency, and space dimensions, where M=min(M_T,M_R), N=max(M_T,M_R), k=ceil M (N-M) . While the DoF outer bound is established for every M_T, M_R value, the achievability is established in general subject to normalization with respect to spatial-extensions. Given spatial-extensions, the achievability relies only on linear beamforming based interference alignment schemes with no need for time frequency extensions. In the absence of spatial extensions, we show through examples how essentially the same scheme may be applied over time frequency extensions. The central new insight to emerge from this work is the notion of subspace alignment chains as DoF bottlenecks. The DoF value d(M,N) is a piecewise linear function of M,N, with either M or N being the bottleneck within each linear segment. The corner points of these piecewise linear segments correspond to A= 1 2,2 3,3 4,... and B= 1 3,3 5,5 7,... . The set A contains all values of M N and only those for which there is redundancy in both M and N. The set B contains all values of M N and only those for which there is no redundancy in either M or N. Our results settle the feasibility of linear interference alignment, introduced by , for the 3 user M_T x M_R MIMO interference channel, completely for all values of M_T, M_R. Specifically, the linear interference alignment problem (M_T x M_R, d)^3 (as defined in previous work by ) is feasible if and only if d<=floor d(M,N) . With and only with the exception of the values M N B, we show that for every M N value there are proper systems that are not feasible. Our results show that M N A are the only values for which there is no DoF benefit of joint processing among co-located antennas at the transmitters or receivers. 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 a new linear physical-layer network coding (LPNC) scheme for fading two-way relay channels. In the uplink phase, two users transmit simultaneously. The relay selects some integer coefficients and computes a linear combination (in a size-q finite set) of the two users' messages, which is broadcast in the downlink phase. We develop a design criterion for choosing the integer coefficients that minimizes the error probability. Based on that, we derive an asymptotically tight bound, in a closed-form, for the error probability of the LPNC scheme over Rayleigh fading channels. Our analysis shows that the error-rate performance of the LPNC scheme becomes asymptotically optimal at a high SNR, and our designed LPNC scheme significantly outperforms existing schemes in the literature. Alternating minimization algorithms are typically used to find interference alignment (IA) solutions for multiple- input multiple-output (MIMO) interference channels with more than K =3 users. For these scenarios many IA solutions exit, and the initial point determines which one is obtained upon convergence. In this paper, we propose a new iterative algorithm that aims at finding the IA solution that maximizes the average sum-rate. At each step of the alternating minimization algorithm, either the precoders or the decoders are moved along the direction given by the gradient of the sum-rate. Since IA solutions are defined by a set of subspaces, the gradient optimization is performed on the Grassmann manifold. The step size of the gradient ascent algorithm is annealed to zero over the iterations in such a way that during the last iterations only the interference leakage is being minimized and a perfect alignment solution is finally reached. Simulation examples are provided showing that the proposed algorithm obtains IA solutions with significant higher throughputs than the conventional IA algorithms. In this paper, we develop the machinery of real interference alignment. This machinery is extremely powerful in achieving the sum degrees of freedom (DoF) of single antenna systems. The scheme of real interference alignment is based on designing single-layer and multilayer constellations used for modulating information messages at the transmitters. We show that constellations can be aligned in a similar fashion as that of vectors in multiple antenna systems and space can be broken up into fractional dimensions. The performance analysis of the signaling scheme makes use of a recent result in the field of Diophantine approximation, which states that the convergence part of the Khintchine-Groshev theorem holds for points on nondegenerate manifolds. Using real interference alignment, we obtain the sum DoF of two model channels, namely the Gaussian interference channel (IC) and the X channel. It is proved that the sum DoF of the K-user IC is (K 2) for almost all channel parameters. We also prove that the sum DoF of the X-channel with K transmitters and M receivers is (K M K + M - 1) for almost all channel parameters. 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. An uplink–downlink two-cell cellular network is studied in which the first base station (BS) with @math antennas receives independent messages from its @math serving users, while the second BS with @math antennas transmits independent messages to its @math serving users. That is, the first and second cells operate as uplink and downlink, respectively. Each user is assumed to have a single antenna. Under this uplink–downlink setting, the sum degrees of freedom (DoFs) is completely characterized as the minimum of @math , @math , @math , and @math , where @math denotes @math . The result demonstrates that, for a broad class of network configurations, operating one of the two cells as uplink and the other cell as downlink can strictly improve the sum DoF compared with the conventional uplink or downlink operation, in which both cells operate as either uplink or downlink. The DoF gain from such uplink–downlink operation is further shown to be achievable for heterogeneous cellular networks having hotspots and with delayed channel state information. 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. In this letter, the degrees of freedom (DoF) outer bound is characterized for an L-cell constant cellular interfering network by using linear interference alignment (IA). For a symmetric network, it means that no matter how many cells and users per cell there are, the total achievable DoF is bounded by M+N, where M and N denote the number of antennas equipped on users and base stations. Besides, a DoF achievable algorithm is also proposed. Although the DoF outer bound cannot be reached, more DoF can be obtained compared with orthogonal schemes. Non-orthogonal multiple access (NOMA) is a strong candidate for next generation radio access networks due to its ability of serving multiple users using the same time and frequency resources. Therefore, researchers in academia and industry have been recently investigating the error performances and capacity of NOMA schemes. The main drawback of NOMA techniques is the interference among users due to the its non-orthogonal access nature, that is usually solved by interference cancellation techniques such as successive interference cancellation (SIC) at the receivers. On the other hand, the interference among users may not be completely eliminated in the SIC process due to the erroneous decisions in the receivers usually caused by channels. In this study, for the first time in the literature, the authors derive an exact closed-form bit error rate (BER) expressions under SIC error for downlink NOMA over Rayleigh fading channels. Besides, they derive one-degree integral form exact BER expressions and closed-form approximate expressions for uplink NOMA. Then, the derived expressions are validated by simulations. The numerical results are depicted to reveal the effects of error during SIC process on the performance for various cases such as power allocation for downlink and channel quality difference for uplink. We consider a single-hop interference network with K transmitters and J receivers, all having M antennas. Each transmitter emits an independent message and each receiver requests an arbitrary subset of the messages. This generalizes the well-known K -user M-antenna interference channel, where each message is requested by a unique receiver. For our setup, we derive the degrees of freedom (DoF) region. The achievability scheme generalizes the interference alignment schemes proposed by Cadambe and Jafar. In particular, we achieve general points in the DoF region by using multiple base vectors and aligning all interferers at a given receiver to the interferer with the largest DoF. As a byproduct, we obtain the DoF region for the original interference channel. We also discuss extensions of our approach where the same region can be achieved by considering a reduced set of interference alignment constraints, thus reducing the time-expansion duration needed. The DoF region for the considered system depends only on a subset of receivers whose demands meet certain characteristics. The geometric shape of the DoF region is also discussed. 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. Narrowband Internet of Things (NB-IoT) is a new narrow-band radio technology introduced in the Third Generation Partnership Project release 13 to the 5th generation evolution for providing low-power wide-area IoT. In NB-IoT systems, repeating transmission data or control signals has been considered as a promising approach for enhancing coverage. Considering the new feature of repetition, link adaptation for NB-IoT systems needs to be performed in 2-D, i.e., the modulation and coding scheme (MCS) and the repetition number. Therefore, existing link adaptation schemes without consideration of the repetition number are no longer applicable. In this paper, a novel uplink link adaptation scheme with the repetition number determination is proposed, which is composed of the inner loop link adaptation and the outer loop link adaptation, to guarantee transmission reliability and improve throughput of NB-IoT systems. In particular, the inner loop link adaptation is designed to cope with block error ratio variation by periodically adjusting the repetition number. The outer loop link adaptation coordinates the MCS level selection and the repetition number determination. Besides, key technologies of uplink scheduling, such as power control and transmission gap, are analyzed, and a simple single-tone scheduling scheme is proposed. Link-level simulations are performed to validate the performance of the proposed uplink link adaptation scheme. The results show that our proposed uplink link adaptation scheme for NB-IoT systems outperforms the repetition-dominated method and the straightforward method, particularly for good channel conditions and larger packet sizes. Specifically, it can save more than 14 of the active time and resource consumption compared with the repetition-dominated method and save more than 46 of the active time and resource consumption compared with the straightforward method.