Interfering Broadcast Channels Research Articles

Joint Optimal Design for Hybrid RIS and DMA Assisted MIMO Interfering Broadcast Channel

Joint Optimal Design for Hybrid RIS and DMA Assisted MIMO Interfering Broadcast Channel

Cellular Networks With Finite Precision CSIT: GDoF Optimality of Multi-Cell TIN and Extremal Gains of Multi-Cell Cooperation

We study the generalized degrees-of-freedom (GDoF) of cellular networks under finite precision channel state information at the transmitters (CSIT). We consider downlink settings modeled by the interfering broadcast channel (IBC) under no multi-cell cooperation, and the overloaded multiple-input-single-output broadcast channel (MISO-BC) under full multi-cell cooperation. We focus on three regimes of interest: the mc-TIN regime, where a scheme based on treating inter-cell interference as noise (mc-TIN) was shown to be GDoF optimal for the IBC; the mc-CTIN regime, where the GDoF region achievable by mc-TIN is convex without the need for time-sharing; and the mc-SLS regime which extends a previously identified regime, where a simple layered superposition (SLS) scheme is optimal for the 3-transmitter-3-user MISO-BC, to overloaded cellular-type networks with more users than transmitters. We first show that the optimality of mc-TIN for the IBC extends to the entire mc-CTIN regime when CSIT is limited to finite precision. The converse proof of this result relies on a new application of aligned images bounds. We then extend the IBC converse proof to the counterpart overloaded MISO-BC, obtained by enabling full transmitter cooperation. This, in turn, is utilized to show that a multi-cell variant of the SLS scheme is optimal in the mc-SLS regime under full multi-cell cooperation, albeit only for 2-cell networks. The overwhelming combinatorial complexity of the GDoF region stands in the way of extending this result to larger networks. Alternatively, we appeal to extremal network analysis, recently introduced by Chan et al., and study the GDoF gain of multi-cell cooperation over mc-TIN in the three regimes of interest. We show that this extremal GDoF gain is bounded by small constants in the mc-TIN and mc-CTIN regimes, yet scales logarithmically with the number of cells in the mc-SLS regime.

On the Optimality of Treating Inter-Cell Interference as Noise: Downlink Cellular Networks and Uplink-Downlink Duality

We consider the information-theoretic optimality of treating inter-cell interference as noise (multi-cell TIN) in downlink cellular networks. We focus on scenarios modeled by the Gaussian interfering broadcast channel (IBC), comprising $K$ mutually interfering Gaussian broadcast channels (BCs), each formed by a base station communicating independent messages to an arbitrary number of users. We establish a new power allocation duality between the IBC and its dual interfering multiple access channel (IMAC), which entails that the corresponding generalized degrees-of-freedom regions achieved through multi-cell TIN and power control (TINA regions) for both networks are identical. As by-products of this duality, we obtain an explicit characterization of the IBC TINA region from a previously established characterization of the IMAC TINA region; and identify a multi-cell convex-TIN regime in which the IBC TINA region is a polyhedron (hence convex) without the need for time-sharing. We then identify a smaller multi-cell TIN regime in which the IBC TINA region is optimal and multi-cell TIN achieves the entire capacity region of the IBC, up to a constant gap. This is accomplished by deriving a new genie-aided outer bound for the IBC, that reveals a novel BC-type order that holds amongst users in each constituent BC (or cell) under inter-cell interference, which in turn is not implied by previously known BC-type orders (i.e. degraded, less noisy and more capable orders). The multi-cell TIN regime that we identify for the IBC coincides with a corresponding multi-cell TIN regime previously identified for the IMAC, hence establishing a comprehensive uplink-downlink duality of multi-cell TIN in the GDoF (and approximate capacity) sense.

Interference Subspace Alignment-Based Precoding Design for Multi-Cell Multi-User Systems

Interference alignment (IA) in the spatial domain has been recognized as an important technique to handle the interference in dense network. However, traditional IA is flawed especially for large scale antenna systems. With challenges brought by hybrid precoding, IA cannot be perfectly achieved with limited radio frequency (RF) chains. In this article, we adopt the thought of interference subspace alignment (ISA) and provide full digital and hybrid precoding schemes for multi-cell multi-user systems under an interfering broadcast channel model. For full digital precoding, we derive the requirement for transmitting antennas to achieve ISA. A closed-form ISA solution space is further developed, where the interference subspace of each user is no longer constrained. Then, a projection-based ISA algorithm is proposed for full digital precoding. The projection from the selfish design to the ISA solution space strengthens the desired signal while achieving ISA. For hybrid precoding, we formulate a vector approximation problem to minimize interference misalignment. A novel generalized gradient projection algorithm is proposed to design each RF chain. To approximately achieve ISA, two algorithms are proposed with different approximation principles. For low SNR, a specific vector in the ISA solution space is approximated to combat additive noise, while for high SNR, the whole ISA solution space is approximated to suppress interference. The proposed schemes are further extended to imperfect CSI cases for more practical scenarios. Simulation results highlight that the proposed full digital and hybrid precoding schemes can effectively handle the inter-cell and intra-cell interference and outperform the existing schemes.

Decentralized User Scheduling for Rate-Constrained Sum-Utility Maximization in the MIMO IBC

While the problems of sum-rate maximization and sum-power minimization subject to quality of service (QoS) constraints in the multiple input multiple output interference broadcast channel (MIMO IBC) have been widely studied, most of the proposed solutions have neglected the user scheduling aspect assuming that a feasible set of users has been previously selected. However, ensuring QoS for each user in the MIMO IBC involves the joint optimization of transmit/receive beamforming vectors, transmit powers, and user scheduling variables. To address the full problem, we propose a novel formulation of a rate-constrained sum-utility maximization problem which allows to either deactivate users or minimize the QoS degradation for some scheduled users in infeasible scenarios. Remarkably, this is achieved avoiding the complexity of traditional combinatorial formulations, but rather by introducing a novel expression of the QoS constraints that allows to solve the problem in a continuous domain. We propose centralized and decentralized solutions, where the decentralized solutions focus on practical design and low signaling overhead. The proposed solutions are then compared with benchmarking algorithms, where we show the effectiveness of the joint scheduling and transceiver design as well as the flexibility of the proposed solution performing advantageously in several MIMO IBC scenarios.

User Scheduling for Sum-Rate Maximization Under Minimum Rate Constraints for the MIMO IBC

While the problem of sum-rate maximization of the multiple-input–multiple-output interference broadcast channel (MIMO IBC) has been extensively studied, most of the proposed solutions do not ensure a minimum rate for each scheduled user. In practice, many services require a minimum rate from the underlying communication links. Therefore, in this letter, we consider a sum-rate maximization problem with per-link minimum rate constraints for the MIMO IBC. The key idea is scheduling a suitable subset of the communication links for simultaneous transmissions, such that a minimum rate for each scheduled link can be ensured. To this end, we pose the sum-rate maximization problem as a combinatorial optimization problem, in which we introduce binary variables to the classical transceiver design problem. We propose a centralized solution based on branch-and-bound and a low-complexity semi-distributed scheme, in which a centralized unit is responsible for scheduling decisions, while the transceiver computations are distributed. Simulations show that the proposed solutions handle the user scheduling effectively, while the proposed semi-distributed scheme performs closely to the centralized scheme.

On the Feasibility of Interference Alignment With Finite Channel Extensions for MIMO Interference Broadcast Channels With Common Messages

In this paper, we analyze the feasibility of interference alignment (IA) schemes with $T$ finite channel extensions for multi-input–multi-output (MIMO) interference broadcast channel (IBC) with common messages, where each base station transmits one common single data stream to all users within its cell. We investigate necessary conditions of feasibility of the IA schemes for this network in three different scenarios, i.e., with no channel extensions ( $T=1$ ), with $T$ ( $T\ge 2$ ) channel extensions for a positive measure of channel coefficients, and with $T$ ( $T \ge 2$ ) dependent channel extensions. These necessary conditions impose constraints on system configurations, e.g., the number of users, the number of antennas, the number of cells, and the number of channel extensions, which must be satisfied when the IA schemes are feasible, and also implicitly provide constraints on the upper bound of degrees of freedom (DoF) with finite channel extensions.

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.

Achievable Sum Rate and Degrees of Freedom of Opportunistic Interference Alignment in MIMO Interfering Broadcast Channels

In this paper, the sum rate of opportunistic interference alignment (OIA) is analyzed in multiple-input-multiple-output interfering broadcast channels. The alignment metric upon which users are scheduled is based on the chordal distance between certain interfering subspaces at each receiver, and the closed-form expressions for the rates of the scheduled users are derived. Furthermore, we show that for a system in which each user has $N$ receive antennas and the $j$ th base station transmits $d_{j}$ data streams, where $\sum _{j=1}^{I}d_{j}={N}+1$ and ${N}\ge 2$ , the rate for each user can be approximated by the mean of a Gumbel random variable. Further analysis reveals that if the number of users in cell $i$ scales as $\rho ^{\alpha }$ , where $\rho $ is the normalized transmit power and $\alpha \in [{0,1}]$ , then cell $i$ can achieve $\alpha d_{i}$ degrees of freedom. The simulation results confirm the validity of the theoretical analysis and the accuracy of the approximation. Thus, the sum rate analysis provided herein is an effective performance evaluation method for multi-cell OIA.

Interference alignment in MIMO interference broadcast channels with imperfect CSI

In this study, the authors propose four interference alignment (IA) schemes for multiple-input multiple-output (MIMO) interference broadcast channels (IBCs) under imperfect channel state information (CSI). They propose two new algorithms based on minimising the leakage of the interference signals under a generalised imperfect CSI model from two new points of view. The first algorithm is based on alternating minimisation algorithm. The second proposed algorithm is an improved version of minimum weighted leakage interference algorithm with a faster convergence rate. Inspired by the CSI uncertainty model, the authors present two robust IA algorithms based on exploiting stochastic properties of the CSI mismatch. The first one is based on joint signal and IA which reduces the leakage of the interference signals outside the interference subspace and forces the intended signal to fall into the orthogonal complement of the interference subspace. The second algorithm maximises the signal-to-interference-plus-noise ratio (SINR) in a per-user-based approach, while the existing maximum SINR (MSINR) algorithm in literature is a per-stream-based approach. The authors illustrate that the proposed MSINR algorithm requires less channel information and has less computational costs compared to the existing MSINR. The superiority of the proposed schemes over the existing algorithms are confirmed by simulation examples.

Degrees of Freedom of Multi-Cell MIMO Interference Broadcast Channels With Distributed Base Stations

Degrees of Freedom of Multi-Cell MIMO Interference Broadcast Channels With Distributed Base Stations

Multi-Agent Distributed Beamforming With Improper Gaussian Signaling for MIMO Interference Broadcast Channels

For rate optimization in interference limited networks, improper Gaussian signaling has shown its ability to outperform conventional proper Gaussian signaling. In this paper, we study a weighted sum-rate maximization problem with improper Gaussian signaling for the multiple-input multiple-output interference broadcast channel. To solve this nonconvex and NP-hard problem, we propose an effective separate covariance and pseudo-covariance matrices optimization algorithm. In the covariance optimization, a weighted minimum mean square error algorithm is adopted, and in the pseudo-covariance optimization, an alternating optimization (AO) algorithm is proposed, which guarantees convergence to a stationary solution and ensures a sum-rate improvement over proper Gaussian signaling. An alternating direction method of multipliers-based multi-agent distributed algorithm is proposed to solve an AO subproblem with the globally optimal solution in a parallel and scalable fashion. The proposed scheme exhibits favorable convergence, optimality, and complexity properties for future large-scale networks. The simulation results demonstrate the superior sum-rate performance of the proposed algorithm as compared with the existing schemes with proper as well as improper Gaussian signaling under various network configurations.

Topological Interference Management for MIMO Interference Broadcast Channels

In this paper, we investigate the topological interference management (TIM) for MIMO interference broadcast channels (IBC) under the fixed topology, where only topology information is needed to cancel the inter-cell interference (ICI). For the single user case, where the MIMO IBC network is reduced to the MIMO interference channel (IC) networks, we propose one novel TIM scheme by exploiting the solution to the corresponding SISO IC TIM based on topology information. And also, we present one theorem to characterize the achievable degrees of freedom (DoFs). For the multiple user case, assuming that each BS not only knows topology information but also knows the channel state information at transmitters (CSIT) within its own cell, we propose two novel TIM schemes, i.e., the virtual user compression-based scheme and the virtual base station extension-based scheme. For each scheme, we design transceivers to cancel both the ICI only based on the topology information by exploiting the solution to the corresponding SISO IC TIM and the multiple user interference (MUI) within its own cell based on the CSIT. Furthermore, we present one theorem to characterize the achievable DoF, respectively. Moreover, we prove that the DoF achieved by the virtual base station extension-based scheme is higher than or equal to that achieved by the virtual user compression-based scheme. Hence, the achievable DoF of MIMO IBC TIM is lower bounded by the optimal DoF attainable for the base station extension scheme. Furthermore, the numerical results show that our schemes can achieve significant performance gain against the traditional interference avoidance scheme.

Beamformer Design for MIMO Interference Broadcast Channels With Semidefinite Programming

We consider beamformer design for multiuser multiple-input multiple-output (MIMO) interference channels where each transmitter communicates to its intended receivers while sharing the same spectro-temporal resources with some other unintended receivers. This scenario is often referred to as MIMO interference broadcast channel (IBC) where by using interference alignment (IA), it is possible to cancel out inter and intracell interferences so that the achievable degrees of freedom could be linearly scaled up with the number of users. In this paper, we propose two distinct and novel IA algorithms, one of which is IA via signal matching (SIGMA) that revolves around interference leakage minimization and further takes the desired signal subspaces into account to output higher sum rates. The second algorithm is called bipartite rank fitting, which is founded on the prior knowledge of the rank of receive beamformers and interference matrices. Therefore, this algorithm is quite a unique approach towards interference alignment in MIMO IBCs since it performs the optimization over only receive beamformers. Furthermore, we propose a robust design of SIGMA algorithm to achieve better performance in the presence of imperfect channel state information (CSI). The key tenet of our design is that we formulate the optimization problems involved in these two algorithms as plain semidefinite programs. It is shown that the proposed algorithms are able to outperform state-of-the-art IA techniques under perfect and imperfect CSI, and the suitability of each algorithm for different network configurations is further discussed.

Interference Alignment Assisted by D2D Communication for the Downlink of MIMO Heterogeneous Networks

To cope with the conflict between the increasing data traffic demands and scarcity of available spectrum resources in wireless networks, multi-tier heterogeneous networks within the same spectrum have been considered to be deployed to provide higher network capacity. However, the spectrum-coexist leads to serious interference. This paper investigates a novel interference alignment (IA) scheme assisted by device-to-device (D2D) communication (DaIA) under a multiple-input multiple-output Gaussian interference broadcast channel heterogeneous scenario. We focus on a hotspot area of communication within the macro cell coverage in which there are two small cells. There is already existing IA algorithm for the case that macro cell base station (BS) has two users. In this paper, we consider different setting that macro cell BS can serve more users. First, as an important aspect of IA, the feasibility conditions for the considered scenario are presented. It acts as a guideline to design the IA scheme. Then the DaIA scheme is proposed to efficiently manage the co-tier interference and inter-tier interference with the reduced channel state information (CSI). Specifically, the proposed DaIA scheme jointly designs precoders and receive filters in closed-form in which the paired users can directly interact with the CSI of interfering channels to design their receiving filters by exploiting D2D communication. Thus the total amount of effective CSI feedback acquired at the BS is greatly reduced. Moreover, we analyze the achievable degrees of freedom of the proposed DaIA scheme. Finally, for the small cells, the precoders and receive filters are further optimized to maximize their achievable rate by combining the water-filling algorithm and the singular value decomposition of the equivalent channel matrix. The simulation results indicate that the proposed DaIA scheme outperforms the conventional interference mitigation schemes.

Topological Interference Management for Wireless Networks

Topological interference management (TIM) is considered under the condition that only topology-related information is available at the transmitters, but no accurate channel state information is fed back to them, which is capable of significantly reducing the overhead imposed on the network. TIM schemes can be classified into two broad categories, relying either on a fixed topology or on alternating connectivity. In this paper, we review the family of TIM schemes. Specifically, for the fixed topology, we discuss the attainable degrees of freedom (DoFs) under the condition that the channel coefficient values are either constant or time varying. For constant channel coefficients, we discuss the multiple groupcast networks/multiple unicast networks, interference channel networks, and interference broadcast channel networks; while for time-varying channel coefficients, we discuss interference channel networks and interference broadcast channel networks. Furthermore, in the context of alternating connectivity, we discuss the attainable DoF for interference channel networks, as well as X networks, vector broadcast channel networks, and interference broadcast channel networks. Finally, promising research directions are identified for TIM schemes.

Sum Rate Analysis for Multi-Cell Random Beamforming With Heterogeneous Schedule Probabilities

In this letter, the closed form sum rate for the random beamforming is analyzed over the downlink multiple-input single-output and multiple input multiple-output interfering broadcast channel with finite users. The analysis approach is based on the limiting throughput distribution theorem, and can be applied for the multi-cell interference scenarios with heterogeneous signal to interference-plus-noise ratio (SINR) distributions and user schedule probabilities. It is proved that both the exact and the asymptotic sum rates achieved from SINR/signal-to-interference ratio analysis will converge to the Gumbel type distribution. The effectiveness of the proposed analytical framework is confirmed by simulation results.

On the Optimality of Multi-User Coordinated Zero-Forcing Beamforming Multicell Systems with Limited Feedback in Interference Channels

An efficient multicell coordinated zero-forcing channel feedback scheme is proposed in this paper. The objective of the proposed feedback design is to control the rate of the user by adaptive allocation of feedback bits of each user as a function of individual channel status thereby keeping the total feedback budge constant. The proposed feedback allocation is studied in interfering broadcast channel (IFBC) and also in time varying channels (TVC) with feedback update duration. First the individual feedback rates of user are derived using convex optimization thereby presenting low complexity algorithm to optimize the channel feedback between inter-user interference and inter-cell interference. The rate offset arising from channel quantization in both IFBC and TVC is investigated by employing the coordinated zero forcing beamforming. Moreover, closed form expressions are derived for necessary feedback scaling and frequency of update duration to achieve the multiplexing gain and throughput. Finally, numerical evaluation results show that the proposed channel feedback schemes outperforms other conventional schemes and assist in base station cooperation management. It can be concluded that frequent update of channel state information and suppression of dominant interferences can yield significant improvements in the sumrate performance of limited feedbback systems.

Low Complexity Interference Alignment for mmWave MIMO Channels in Three-Cell Mobile Network

Millimeter wave (mmWave) communications are an important candidate technique in 5G networks for features, supporting ultra-dense small cells and mobile data offloading. However, ultra-dense nodes and increasing data traffic bring in vast interference. This paper investigates low complexity non-iterative interference alignment (IA) schemes for multiple-input multiple-output (MIMO) interference broadcast channels in mmWave communications. The authors focus on the three-cell mobile network model in which each base station supports no more than two users within its cell. There is already a closed-form IA solution for the case that one cell has two users, while the other two have one user in each, which can be denoted as {2,1,1}. This paper considers different settings and proposes corresponding IA schemes. First, two IA schemes based on multi-step for the asymmetric setting {2,2,1} are presented, five degree of freedom (DoF) could be achieved. Then, for the symmetric setting {2,2,2}, a novel IA solution with lower complexity and a joint method combining IA with non-iterative multi-user MIMO technique are proposed, and they can achieve six DoF. The simulation results indicate that our non-iterative schemes have similar sum-rate capacity performances with the iterative ones in existing work, and the complexity is effectively reduced.

Weighted sum rate maximization in MIMO interfering broadcast channels exploiting virtual per‐user power constraints

AbstractIn this paper, we consider the weighted sum rate (WSR) maximization problem in a partially coordinated multiple‐input multiple‐output multicell broadcast channel with constraints on base stations' transmit powers where the communication is based on dirty paper coding. To be able to obtain a computationally efficient solution for this non‐convex optimization problem, we solve it by a fast algorithm for WSR maximization under per‐user power constraints. The main idea is to define virtual per‐user power constraints that add up to the per‐base station power budgets in each cell and optimize the per‐user power constraints to maximize the WSR. We propose two computationally efficient power allocation algorithms to find the per‐user power constraints, namely, the waterfilling‐based power update and the gradient descent–based power update algorithms. In the latter one, we find a closed‐form expression for the derivative of the maximum of WSR wrt the per‐user power constraints resulting in a considerable reduction in the complexity. The resulting algorithms are computationally efficient, and our simulation results show that they achieve significantly higher bit rates than the current algorithms at the same signal‐to‐noise power ratio.