Multiple-access Interference Channel Research Articles

Twin Delayed DDPG based Dynamic Power Allocation for Mobility in IoRT

The internet of robotic things (IoRT) is a modern as well as fast-evolving technology employed in abundant socio-economical aspects which connect user equipment (UE) for communication and data transfer among each other. For ensuring the quality of service (QoS) in IoRT applications, radio resources, for example, transmitting power allocation (PA), interference management, throughput maximization etc., should be efficiently employed and allocated among UE. Traditionally, resource allocation has been formulated using optimization problems, which are then solved using mathematical computer techniques. However, those optimization problems are generally nonconvex as well as nondeterministic polynomial-time hardness (NP-hard). In this paper, one of the most crucial challenges in radio resource management is the emitting power of an antenna called PA, considering that the interfering multiple access channel (IMAC) has been considered. In addition, UE has a natural movement behavior that directly impacts the channel condition between remote radio head (RRH) and UE. Additionally, we have considered two well-known UE mobility models i) random walk and ii) modified Gauss-Markov (GM). As a result, the simulation environment is more realistic and complex. A data-driven as well as model-free continuous action based deep reinforcement learning algorithm called twin delayed deep deterministic policy gradient (TD3) has been proposed that is the combination of policy gradient, actor-critics, as well as double deep Q-learning (DDQL). It optimizes the PA for i) stationary UE, ii) the UE movements according to random walk model, and ii) the UE movement based on the modified GM model. Simulation results show that the proposed TD3 method outperforms model-based techniques like weighted MMSE (WMMSE) and fractional programming (FP) as well as model-free algorithms, for example, deep Q network (DQN) and DDPG in terms of average sum-rate performance.

A Novel Tri-Staged RIA Scheme for Cooperative Cell Edge Users in a Multi-Cellular MIMO IMAC

In the real world of wireless communication systems, one solution to the practical limitation of interference alignment in terms of global channel state information at the transmitter (CSIT) requirement is to consider a linear precoding approach that only uses delayed CSIT known as retrospective interference alignment (RIA). Therefore, in the proposed work, a novel RIA scheme for the cooperative cell edge (CE) users that are more vulnerable to inter-cell interference in a multi-cellular multiple-input multiple-output (MIMO) interference multiple access channels (IMAC) is presented. The core idea of the proposed RIA is characterized by interference refining at the end of the first two stages and interference redirecting at the third stage. The initial stage 1 involves feeding the base station (BS) in cell-1 with the data streams from the cooperative CE users. During stage 2, the BS in cell-2 is fed with data streams from the cooperative CE users in cell-2. In the final stage 3, the overheard equation redirecting is performed. Based on the proposed method, we showed that for a three CE user cooperative multi-cellular MIMO IMAC channel, the achievable degrees of freedom (DoF) is 24/7 and later extended to a general L CE user cooperative multi-cellular MIMO IMAC channel and obtained the desired DoF as 2L(L+1)/2L+1. The simulation result shows that in comparison with the other benchmark schemes considered, the proposed scheme provides a greater DoF and thereby enhances the performance of cooperative CE users.

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.

Constant-Gap-to-Capacity and Generalized Degrees of Freedom Regions of the MIMO MAC-IC-MAC

The MAC-IC-MAC is a class of multiple-access interference channels consisting of two multiple-access channels (MACs) that are mutually interfering but in which there is interference only from one transmitter of each MAC to the receiver of the other MAC. Two achievable rate regions that are within a quantifiable gap of the capacity region for the discrete-memoryless semi-deterministic MAC-IC-MAC were obtained in a previous companion work by the authors using inner and outer bounds that are unions of polytopes over admissible random coding distributions. In this paper, we obtain single-distribution—and hence explicit—inner and outer bounds that characterize the capacity region of the MIMO Gaussian MAC-IC-MAC to within a constant gap. We also evaluate and study the generalized degrees of freedom (GDoF) region via multidimensional signal-level partitioning for MIMO networks. Through its lens, the achievability of the key vertices of the GDoF region are examined. This analysis as well as the symmetric GDoF curve reveal that, at high SNR, when the ratio of the interference-to-noise to the signal-to-noise ratios, both taken in dB, is within a certain range, non-interfering transmitters in that cell can fully occupy the receivers’ signal partitions in one or more dimensions that cannot otherwise be utilized by the interfering transmitter alone. This extends the same finding in the companion paper which established the results of this work for the scalar Gaussian MAC-IC-MAC.

On the Optimality of Treating Inter-Cell Interference as Noise in Uplink Cellular Networks

In this paper, we explore the information-theoretic optimality of treating interference as noise (TIN) in cellular networks. We focus on uplink scenarios modeled by the Gaussian interfering multiple access channel (IMAC), comprising $K$ mutually interfering multiple access channels (MACs), each formed by an arbitrary number of transmitters communicating independent messages to one receiver. We define TIN for this setting as a scheme in which each MAC (or cell) performs a power-controlled version of its capacity-achieving strategy, with Gaussian codebooks and successive decoding, while treating interference from all other MACs (i.e., inter-cell interference) as noise. We characterize the generalized degrees-of-freedom (GDoF) region achieved through the proposed TIN scheme, and then identify conditions under which this achievable region is convex without the need for time-sharing. We then tighten these convexity conditions and identify a regime in which the proposed TIN scheme achieves the entire GDoF region of the IMAC and is within a constant gap of the entire capacity region.

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.

Optimal Multiuser Diversity in Multi-Cell MIMO Uplink Networks: User Scaling Law and Beamforming Design

We introduce a distributed protocol to achieve multiuser diversity in a multicell multiple-input multiple-output (MIMO) uplink network, referred to as a MIMO interfering multiple-access channel (IMAC). Assuming both no information exchange among base stations (BS) and local channel state information at the transmitters for the MIMO IMAC, we propose a joint beamforming and user scheduling protocol, and then show that the proposed protocol can achieve the optimal multiuser diversity gain, i.e., KMlog(SNRlog N), as long as the number of mobile stations (MSs) in a cell, N, scales faster than SNR K M − L 1 − ϵ for a small constant ϵ > 0, where M, L, K, and SNR denote the number of receive antennas at each BS, the number of transmit antennas at each MS, the number of cells, and the signal-to-noise ratio, respectively. Our result indicates that multiuser diversity can be achieved in the presence of intra-cell and inter-cell interference even in a distributed fashion. As a result, vital information on how to design distributed algorithms in interference-limited cellular environments is provided.

Opportunistic Interference Alignment in Poor Scattering Channels

Opportunistic interference alignment (OIA) is known to achieve the optimal degrees of freedom (DoF) in the interfering multiple-access channel (IMAC) with independent and identically distributed (i.i.d.) Rayleigh fading, provided that a certain user scaling condition is satisfied. We analyze the performance of OIA in a poor scattering K-cell single-input multiple-output IMAC, where there exist finite paths between the transmitter and receiver sides. Under the feasible model, we characterize a lower bound on the cumulative density function (cdf) of the leakage of interference (LIF) generated by each mobile station (MS) and then derive a new fundamental user scaling law that is, required to achieve a target DoF, which generalizes the existing achievability result shown for the i.i.d. Rayleigh fading case. Our main result indicates that KS DoF is achievable if the number of per-cell MSs scales at least as SNR <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(K-1)\min(L,S)</sup> , where L denotes the number of paths and S denotes the number of simultaneously transmitting MSs per cell. We also show how to obtain the non-integer DoF when the above user scaling condition is not strictly satisfied for given system parameters. To verify our achievability result for finite system parameters, computer simulations are performed along with comparison to the i.i.d. Rayleigh channel case. The amount of LIF is first evaluated numerically and is shown to be consistent with our theoretical result. The achievable sum rates are also evaluated.

Capacity-Achieving Input Distributions of Additive Quadrature Gaussian Mixture Noise Channels

This paper studies the characterization of the optimal input and the computation of the capacity of additive quadrature Gaussian mixture (GM) noise channels under an average power constraint. The considered model can be used to represent a wide variety of channels with impulsive interference, such as the well-known Bernoulli-Gaussian and Middleton class-A impulsive noise channels, as well as multiple-access interference channels and cognitive radio channels under imperfect sensing. At first, we demonstrate that there exists a unique input distribution that achieves the channel capacity, and the capacity-achieving input distribution has a uniformly distributed phase. By examining the Kuhn-Tucker alignment conditions (KTCs), we further show that, if the optimal input amplitude distribution contains an infinite number of mass points on a bounded interval, the channel output must be Gaussian-distributed. However, by using Bernstein's theorem to examine the completely monotonic condition, it is shown that the assumption of a Gaussian-distributed output is not valid. As a result, there are always a finite number of mass points on any bounded interval in the optimal amplitude distribution. In addition, by applying a novel bounding technique on the KTC and using the envelop theorem, we demonstrate that the optimal amplitude distribution cannot have an infinite number of mass points. This gives us the unique solution of the optimal input having discrete amplitude with a finite number of mass points. Given this discrete nature of the optimal input, we then develop a simple method to compute the discrete optimal input and the corresponding capacity. Our numerical examples show that, in many cases, the capacity-achieving distribution consists of only one or two mass points.

Retrospective Interference Alignment for the Two-Cell MIMO Interfering Multiple Access Channel

In this paper, we propose a new retrospective interference alignment for two-cell multiple-input multiple-output (MIMO) interfering multiple access channels (IMAC) with $M$ receive antennas per base station (BS) and $K$ users per cell each with $N$ transmit antennas. The key idea of the retrospective IA lies in interference-purification during phase 1 and 2, and interference-repetition during phase 3. On the basis of the proposed method, we show that the achievable sum degrees of freedom (sum-DoF) is equal to $2M\left(\left\lceil\frac{2M}{N}\right\rceil+1\right)/\left(2\left\lceil\frac{2M}{N} \right\rceil+1\right)$ if $K\le M and $\min\{2KN,M\}$ if $NK \le M$ with completely delayed channel state information at the transmitters (CSIT) . It is shown that having delayed CSIT can strictly increase the sum-DoF compared to the case with no CSIT for cellular networks, especially for uplink scenarios.

New Interference Alignment Algorithms Based on Desired Signals for Two-Cell MIMO Interfering Multiple-Access Channels

In this paper, we propose two new iterative algorithms termed maximum-power interference alignment (MP-IA) and maximum-SINR IA (MSINR-IA) in two-cell multiple-input multiple-output (MIMO) interfering multiple-access channels (IMACs) which optimize the IA reference vectors from the perspective of maximizing the effective power of the desired signals and received signal to interference and noise (SINR), respectively. Under perfect feedback as well as limited feedback scenarios, the proposed schemes are evaluated in terms of the average sum rate and bit error rate (BER) performance and the simulation results show the advantages of the proposed schemes over existing algorithms.

A Closed-Form Solution to Implement Interference Alignment and Cancellation for a Gaussian Interference Multiple Access Channel

For interference alignment (IA) with no channel extension, determining the existence of IA solution for general system parameters is still an open problem. This same problem also exists in interference alignment and cancellation (IAC), which combines IA with interference cancellation in the receivers, involving a new receiver architecture associated with signaling over backhaul links among them. As IAC is expected to achieve more degrees of freedom (DoF) than IA, the existence of IAC solution would be another interesting, yet challenging issue to investigate. In this paper, we have proposed a specific alignment scheme, which allows for the derivation of closed-form IAC solution. Furthermore, we establish and prove the general necessary and sufficient condition to determine the existence of closed-form IAC solution for a Gaussian interference multiple access channel (MAC) with K receivers and J users, each with M antennas.

Codebook-Based Opportunistic Interference Alignment

For the multiple-input multiple-output interfering multiple-access channels (IMACs), opportunistic interference alignment (OIA) using the singular value decomposition (SVD)-based beamforming at each user fundamentally reduces the user scaling condition required to achieve any target DoF, compared to that for the single-input multiple-output IMAC. In this paper, we tackle two practical challenges of the existing SVD-based OIA: 1) the need of full feedforward of the selected users' beamforming weight vectors and 2) a low rate achieved based on the exiting zero-forcing receiver. We first propose a codebook-based OIA, in which the weight vectors are chosen from a predefined codebook with a finite size so that information of the weight vectors can be sent to the belonging BS with limited feedforward. We derive the codebook size required to achieve the same user scaling condition as the SVD-based OIA case for both Grassmannian and random codebooks. Surprisingly, it is shown that the derived codebook size is the same for the two codebook methods. Second, we introduce an enhanced receiver at the base stations (BSs) in pursuit of further improving the achievable rate. Assuming no collaboration between the BSs, the interfering links between a BS and the selected users in neighboring cells are difficult to be acquired at the belonging BS. We propose the use of a simple minimum Euclidean distance receiver operating with no information of the interfering links. With the help of the OIA, we show that this new receiver asymptotically achieves the channel capacity as the number of users increases.

Opportunistic Interference Alignment for MIMO Interfering Multiple-Access Channels

We consider the K-cell multiple-input multiple-output (MIMO) interfering multiple-access channel (IMAC) with time-invariant channel coefficients, where each cell consists of a base station (BS) with M antennas and N users having L antennas each. In this paper, we propose two opportunistic interference alignment (OIA) techniques utilizing multiple transmit antennas at each user: antenna selection-based OIA and singular value decomposition (SVD)-based OIA. Their performance is analyzed in terms of user scaling law required to achieve KS degrees-of-freedom (DoF), where S(≤ M) denotes the number of simultaneously transmitting users per cell. We assume that each selected user transmits a single data stream at each time-slot. It is shown that the antenna selection-based OIA does not fundamentally change the user scaling condition if L is fixed, compared with the single-input multiple-output (SIMO) IMAC case, which is given by SNR <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(K-1)S</sup> , where SNR denotes the signal-to-noise ratio. In addition, we show that the SVD-based OIA can greatly reduce the user scaling condition to SNR <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(K-1)S-L+1</sup> through optimizing a weight vector at each user. Simulation results validate the derived scaling laws of the proposed OIA techniques. The sum-rate performance of the proposed OIA techniques is compared with the conventional techniques in MIMO IMAC channels and it is shown that the proposed OIA techniques outperform the conventional techniques.

Groupwise Frequency Domain Multiuser MMSE Turbo Equalization for Single Carrier Block Transmission Over Spatially Correlated Channels

This paper proposes a novel turbo equalization scheme based on groupwise soft interference cancelling minimum mean-squared error filtering (SC-MMSE) combined with maximum a posteriori signal detection for multiple access single-carrier block transmission. For an efficient implementation of the equalizer, the linear groupwise SC-MMSE filter is directly derived in the frequency domain by introducing an additional design criterion in the optimization. Special focus is given on different heuristic methods for group selection based on mean-squared error (MSE) and spatial channel correlation criteria. The first method dynamically forms groups incorporating a priori information at each turbo iteration, while the second and third methods provide a static grouping that is valid for all turbo iterations. Results of correlation chart analysis and bit error rate simulations demonstrate that the groupwise turbo frequency domain equalizer (FDE) achieves a large performance gain over the conventional SC-MMSE FDE in intersymbol interference multiple access channels with high spatial correlation among the multiple users' transmitted signals. Moreover, it is shown that the simple static correlation-based grouping scheme when applied to the proposed receiver achieves similar performance than the dynamic MSE-based scheme at a significantly reduced complexity. In addition, to assess the practicality of the novel algorithm in real scenarios, we show numerical results obtained by a series of simulations using channel-sounding field measurement data.

A novel zonal UWB receiver with superior performance

A novel ultra-wide bandwidth receiver structure dubbed the receiver is based on the qualitative nature of the probability density function of the multiple access interference. It is proposed for time-hopping ultra-wide bandwidth wireless signal detection in multiple access interference channels. In ideal free-propagation channels, the zonal receiver always meets or outperforms the conventional matched filter UWB receiver, the recently proposed soft-limiting UWB receiver and its enhanced version, the adaptive threshold soft-limiting UWB receiver. A new Rake receiver design based on the zonal receiver is proposed for signal detection in multipath fading channels. Simulation results and analysis show that this new Rake receiver can achieve larger signal-to-interference-plus-noise ratio than the standard matched filter Rake receiver when multipath components are resolvable in UWB channels.

P-order metric UWB receiver structures with superior performance

The generalized Gaussian probability density function is shown to better approximate the probability density function of the multiple access interference in ultra-wide bandwidth systems than the Gaussian approximation and the Laplacian density approximation. Two ultra-wide bandwidth receiver structures based on this new approximation using a p-order metric receiver decision statistic are investigated for the detection of time-hopping ultra-wide bandwidth wireless signals in multiple access interference channels. The first receiver outperforms both the conventional matched filter ultra-wide bandwidth receiver and the soft-limiting ultra-wide bandwidth receiver when only multiple access interference is present in UWB channels. The second new receiver with adaptive limiting threshold outperforms the conventional matched filter ultra-wide bandwidth receiver, the soft-limiting ultra-wide bandwidth receiver, and the adaptive threshold soft limiting ultra-wide bandwidth receiver in all multiple access interference-plus-noise environments. In multipath channels, a new Rake receiver based on the p-order metric receiver is proposed for signal detection. Mathematical analysis and numerical results show that this new Rake receiver can achieve larger signal-to-interference-plus-noise ratio than the standard matched filter Rake receiver when multipath components are resolvable in UWB channels.

Algebraic properties of space-time block codes in intersymbol interference multiple-access channels

In this paper, we study the multiple-access channel where users employ space-time block codes (STBC). The problem is formulated in the context of an intersymbol interference (ISI) multiple-access channel which occurs for transmission over frequency-selective channels. The algebraic structure of the STBC is utilized to design joint interference suppression, equalization, and decoding schemes. Each of the K users transmits using M/sub t/=2 transmit antennas and a time-reversed STBC suitable for frequency-selective channels. We first show that a diversity order of 2M/sub r/(/spl nu/+1) is achievable at full transmission rate for each user, when we have M/sub r/ receive antennas, channel memory of /spl nu/, and an optimal multiuser maximum-likelihood (ML) decoder is used. Due to the decoding complexity of the ML detector we study the algebraic structure of linear multiuser detectors which utilize the properties of the STBC. We do this both in the transform (D-domain) formulation and when we impose finite block-length constraints (matrix formulation). The receiver is designed to utilize the algebraic structure of the codes in order to preserve the block quaternionic structure of the equivalent channel for each user. We also explore some algebraic properties of D-domain quaternionic matrices and of quaternionic circulant block matrices that arise in this study.