Inter-cluster Interference Research Articles

Inter-Cluster Design of Wireless Fronthaul and Access Links for the Downlink of C-RAN

This letter studies the joint design of wireless fronthaul and radio access links for the downlink of a cloud radio access network (C-RAN). In a C-RAN, high spectral efficiency can be achieved by migrating the baseband processing functionalities to a baseband processing unit (BBU). However, due to the increased system cost, the size of cluster should be kept relatively small, and hence the spectral efficiency performance tends to be limited by the impact of inter-cluster interference signals. This letter tackles the problem of jointly optimizing the fronthaul and access links across multiple clusters with the goal of maximizing the sum-rate of all the user equipments belonging to the clusters while satisfying the power constraints at the BBUs and remote radio heads. Via numerical results, the effectiveness of the proposed algorithm is confirmed.

Interference Alignment in Two-Tier Randomly Distributed Heterogeneous Wireless Networks Using Stochastic Geometry Approach

With the massive increase in wireless data traffic in recent years, multi-tier wireless networks have been deployed to provide much higher capacities and coverage. However, heterogeneity of wireless networks bring new challenges for interference analysis and coordination due to spatial randomly distributed transmitters. In this paper, we present a distance-dependent interference alignment (IA) approach for a generic two-tier heterogeneous wireless network, where transmitters in the first and second tiers are distributed as poisson point process (PPP) and poisson cluster process, respectively. The feasibility condition of the IA approach is used to find upper bound of the number of interference streams that can be aligned. The proposed IA scheme maximizes the second-tier throughput by using the tradeoff between signal-to-interference ratio and multiplexing gain. It is shown that acquiring accurate knowledge of the distance between the receiver in the second-tier and the nearest cross-tier transmitter only brings insignificant throughput gain compared with statistical knowledge of distance. Furthermore, the remaining cross-tier and intercluster interferences are modeled and analyzed using stochastic geometry technique. Numerical results validate the derived expressions of success probabilities and throughput, and show that the distance-dependent IA scheme significantly outperforms the traditional IA scheme in the presence of path-loss effect.

Non-Orthogonal Multiple Access (NOMA) for Downlink Multiuser MIMO Systems: User Clustering, Beamforming, and Power Allocation

We investigate the application of non-orthogonal multiple access (NOMA) with successive interference cancellation (SIC) in downlink multiuser multiple-input multiple-output (MIMO) cellular systems, where the total number of receive antennas at user equipment (UE) ends in a cell is more than the number of transmit antennas at the base station (BS). We first dynamically group the UE receive antennas into a number of clusters equal to or more than the number of BS transmit antennas. A single beamforming vector is then shared by all the receive antennas in a cluster. We propose a linear beamforming technique in which all the receive antennas can significantly cancel the inter-cluster interference. On the other hand, the receive antennas in each cluster are scheduled on the power domain NOMA basis with SIC at the receiver ends. For inter-cluster and intra-cluster power allocation, we provide dynamic power allocation solutions with an objective to maximizing the overall cell capacity. An extensive performance evaluation is carried out for the proposed MIMO-NOMA system and the results are compared with those for conventional orthogonal multiple access (OMA)-based MIMO systems and other existing MIMO-NOMA solutions. The numerical results quantify the capacity gain of the proposed MIMO-NOMA model over MIMO-OMA and other existing MIMO-NOMA solutions.

Modeling and Analysis of Uplink Non-Orthogonal Multiple Access (NOMA) in Large-Scale Cellular Networks Using Poisson Cluster Processes

Using the theory of Poisson cluster process (PCP), this paper provides a framework to analyze multi-cell uplink non-orthogonal multiple access (NOMA) systems. Specifically, we characterize the rate coverage probability of an NOMA user who is at rank $m$ (in terms of the distance from its serving base station) among all users in a cell and the mean rate coverage probability of all users in a cell. Since the signal-to-interference-plus-noise ratio of the $m$ th user relies on efficient successive interference cancellation (SIC), we consider three scenarios, i.e., perfect SIC (in which the signals of $m-1$ interferers who are stronger than the $m$ th user are decoded successfully), imperfect SIC (in which the signals of $m-1$ interferers who are stronger than the $m$ th user may or may not be decoded successfully), and imperfect worst case SIC (in which the decoding of the signal of the $m$ th user is always unsuccessful whenever the decoding of its relative $m-1$ stronger users is unsuccessful). To derive the rate coverage expressions, we first characterize the Laplace transforms of the intra-cluster interferences in closed-form considering various SIC scenarios. The Laplace transform of the inter-cluster interference is then characterized by exploiting distance distributions from geometric probability. The derived expressions are customized for an equivalent OMA system. Finally, numerical results are presented to validate the derived expressions. The worst case SIC assumption provides remarkable simplifications in the mathematical analysis and is found to be highly accurate for higher user target rate requirements. A comparison of Poisson point process-based and PCP-based modeling is also conducted.

On the Virtual Cell Transmission in Ultra Dense Networks

Ultra dense networks (UDN) are identified as one of the key enablers for 5G, since they can provide an ultra high spectral reuse factor exploiting proximal transmissions. By densifying the network infrastructure equipment, it is highly possible that each user will have one or more dedicated serving base station antennas, introducing the user-centric virtual cell paradigm. However, due to irregular deployment of a large amount of base station antennas, the interference environment becomes rather complex, thus introducing severe interferences among different virtual cells. This paper focuses on the downlink transmission scheme in UDN where a large number of users and base station antennas is uniformly spread over a certain area. An interference graph is first created based on the large-scale fadings to give a potential description of the interference relationship among the virtual cells. Then, base station antennas and users in the virtual cells within the same maximally-connected component are grouped together and merged into one new virtual cell cluster, where users are jointly served via zero-forcing (ZF) beamforming. A multi-virtual-cell minimum mean square error precoding scheme is further proposed to mitigate the inter-cluster interference. Additionally, the interference alignment framework is proposed based on the low complexity virtual cell merging to eliminate the strong interference between different virtual cells. Simulation results show that the proposed interference graph-based virtual cell merging approach can attain the average user spectral efficiency performance of the grouping scheme based on virtual cell overlapping with a smaller virtual cell size and reduced signal processing complexity. Besides, the proposed user-centric transmission scheme greatly outperforms the BS-centric transmission scheme (maximum ratio transmission (MRT)) in terms of both the average user spectral efficiency and edge user spectral efficiency. What is more, interference alignment based on the low complexity virtual cell merging can achieve much better performance than ZF and MRT precoding in terms of average user spectral efficiency.

Mitigating inter-cluster interference on the uplink for a three-cell clustered cooperative network

In this paper, we propose a practical and scalable solution to mitigating interference on the uplink through static clustering and adaptive fractional frequency reuse (CFFR). The focus is on a three-cell clustered network due to its low complexity. Moreover, we have previously shown that a performance comparable to that of global coordination is achievable using a cluster size of three. In this paper, for a clustered planar Wyner network, we derive analytical capacity equations for zero forcing (ZF) and linear minimum mean squared error (LMMSE)-based receivers. The theoretical results show that inter-cluster interference is the major performance bottleneck and that the smallest interference from the neighbouring clusters is sufficient to significantly lower the system performance. We then switch our study to a more realistic network setting and augment our CFFR technique by adopting an entirely distributed architecture and by implementing a location classification algorithm based on logistic regression. We then show through simulations that CFFR performs significantly better than the widely studied dynamic clustering (DC) technique. Since the inter-cluster interference intensity of CFFR is much lower than DC, the per-cell sum rate performance is 1.5 × better, especially at high loads. We also show that the CFFR algorithm is a lot less complex than DC in terms of running time.

A Stochastic Analysis of Network MIMO Systems

This paper quantifies the benefits and limitations of cooperative communications by providing a statistical analysis of the downlink in network multiple-input multiple-output (MIMO) systems. We consider an idealized model where the multiple-antenna base-stations (BSs) are distributed according to a homogeneous Poisson point process and cooperate by forming disjoint clusters. We assume that perfect channel state information (CSI) is available at the cooperating BSs without any overhead. Multiple single-antenna users are served using zero-forcing beamforming with equal power allocation across the beams. For such a system, we obtain tractable, but accurate, approximations of the signal power and inter-cluster interference power distributions and derive a computationally efficient expression for the achievable per-BS ergodic sum rate using tools from stochastic geometry. This expression allows us to obtain the optimal loading factor, i.e., the ratio between the number of scheduled users and the number of BS antennas, that maximizes the per-BS ergodic sum rate. Further, it allows us to quantify the performance improvement of network MIMO systems as a function of the cooperating cluster size. We show that to perform zero-forcing across the distributed set of BSs within the cluster, the network MIMO system introduces a penalty in received signal power. Along with the inevitable out-of-cluster interference, we show that the per-BS ergodic sum rate of a network MIMO system does not approach that of an isolated cell even at unrealistically large cluster sizes. Nevertheless, network MIMO does provide significant rate improvement as compared to uncoordinated single-cell processing even at relatively modest cluster sizes.

Hierarchical Resource Allocation Framework for Hyper-Dense Small Cell Networks

This paper considers joint power control and subchannel allocation for co-tier interference mitigation in extremely dense small cell networks, which is formulated as a combinatorial optimization problem. Since it is intractable to obtain the globally optimum assignment policy for existing techniques due to the huge computation and communication overheads in ultra-dense scenario, in this paper, we propose a hierarchical resource allocation framework to achieve a desirable solution. Specifically, the solution is obtained by dividing the original optimization problem into four stages in partially distributed manner. First, we propose a divide-and-conquer strategy by invoking clustering technique to decompose the dense network into smaller disjoint clusters. Then, within each cluster, one of the small cell access points is elected as a cluster head to carry out intra-cluster subchannel allocation with a low-complexity algorithm. To tackle the issue of inter-cluster interference, we further develop a distributed learning-base coordination mechanism. Moreover, a local power adjustment scheme is also presented to improve the system performance. Numerical results verify the efficiency of the proposed hierarchical scheme, and demonstrate that our solution outperforms the state-of-the-art methods, especially for hyper-dense networks.

Joint dynamic clustering and user scheduling for downlink cloud radio access network with limited feedback

In limited feedback-based Cloud-RAN (C-RAN) systems, the inter-cluster and intra-cluster interference together with the quantification error can seriously deteriorates the system spectral efficiency. We, in this paper, propose an efficient three-phase framework and corresponding algorithms for dealing with this problem. Firstly, a greedy scheduling algorithm based on the lower bound of the ergodic rate is performed for generating an elementary cluster in the first phase. And then the elementary cluster is divided into many small clusters according to the following proposed algorithms based on the short term instantaneous information in the second phase. In the end, based on the limited feedback two zero-forcing (ZF) precoding strategies are adopted for reducing the intra-cluster interference in the third phase. The provided Monte Carlo simulations show the effectiveness of our proposed algorithms in the respect of system spectral efficiency and average user rate.

An AdaptiveTDMA Slot Assignment Strategy in Vehicular Ad Hoc Networks

Improving road safety is among the main objectives of Vehicular Ad-hoc NETworks (VANETs) design. This objective would be achieved essentially by the use of efficient safety applications which should be able to wirelessly broadcast warning messages between neighbouring vehicles in order to inform drivers about a dangerous situation in a timely manner. To insure their efficiency, safety applications require reliable periodic data dissemination with low latency. Medium Access Control (MAC) protocols play a primary role to provide efficient delivery and avoid as much as possible data packet loss. In fact, in distributed MAC approaches, packet loss is a consequence of collisions resulted from well known situations of the exposed and hidden node situations. This paper introduces an Adaptive TDMA Slot Assignment Strategy (ASAS) for VANET based on clustering of vehicles. The main aim of this work is to provide a MAC layer protocol that can reduce inter-cluster interference under different traffic loading conditions without having to use expensive spectrum and complex mechanisms such as CDMA or OFDMA. An analysis and simulation results are presented to evaluate the performance of ASAS. Moreover, we compare its performance with two TDMA MAC protocols DMMAC and VeMAC

Green Inter-Cluster Interference Management in Uplink of Multi-Cell Processing Systems

This paper examines the uplink of cellular systems employing base station cooperation for joint signal processing. We consider clustered cooperation and investigate effective techniques for managing inter-cluster interference to improve users' performance in terms of both spectral and energy efficiency. We use information theoretic analysis to establish general closed form expressions for the system achievable sum rate and the users' Bit-per-Joule capacity while adopting a realistic user device power consumption model. Two main inter-cluster interference management approaches are identified and studied, i.e., through: 1) spectrum re-use; and 2) users' power control. For the former case, we show that isolating clusters by orthogonal resource allocation is the best strategy. For the latter case, we introduce a mathematically tractable user power control scheme and observe that a green opportunistic transmission strategy can significantly reduce the adverse effects of inter-cluster interference while exploiting the benefits from cooperation. To compare the different approaches in the context of real-world systems and evaluate the effect of key design parameters on the users' energy-spectral efficiency relationship, we fit the analytical expressions into a practical macrocell scenario. Our results demonstrate that significant improvement in terms of both energy and spectral efficiency can be achieved by energy-aware interference management.

Phase Only RF Precoding for Massive MIMO Systems With Limited RF Chains

Massive MIMO systems promise high spectrum efficiency by deploying <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$M \gg 1$</tex></formula> antennas at the base station (BS). However, to achieve the full gain provided by massive MIMO, the BS requires <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$M$</tex> </formula> radio frequency (RF) chains, which are expensive. This motivates us to consider RF-chain limited massive MIMO systems with <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$M$</tex> </formula> antennas but only <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$S \ll M$</tex></formula> RF chains. We propose a two-stage precoding scheme to efficiently exploit the large spatial degree of freedom (DoF) gain in massive MIMO systems with limited RF chains and reduced channel state information (CSI) signaling overhead. In this scheme, the MIMO precoder is partitioned into a high-dimensional phase only RF precoder followed by a low-dimensional baseband precoder. The RF precoder is adaptive to the spatial correlation matrices for inter-cluster interference mitigation. The baseband precoder is adaptive to the reduced dimensional “effective” CSI for intra-cluster spatial multiplexing. We formulate the two stage precoding problem such that the minimum (weighted) average data rate of users is maximized under the phase only constraint on the RF precoder and the limited RF chain constraint. This is a combinatorial optimization problem which is in general NP-hard. We propose a low complexity solution based on a novel bi-convex approximation approach. Simulations show that the proposed design has significant gain over various baselines.

Clustering for Interference Alignment in Multiuser Interference Network

Interference alignment (IA) has been shown to be a promising technique for achieving the optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). However, in practical communication systems, mitigating interference from all interferers via IA is not necessary since some users' interference have negligible effect due to large path-loss. Moreover, the feasibility constraint and the heavy signaling overhead hinder applying IA on interference from all interferers. Clustered IA puts users in disjoint clusters where IA is applied to users within each cluster. It provides a mechanism for mitigating the signaling overhead and maximizing the achievable rate. However, how to properly form IA clusters has not been well studied. We consider the application of clustered IA in a multiuser interference network with asymmetric channel attenuation at finite SNR. We model the interference network as a connected graph, transforming the clustering problem into a graph partitioning problem. By exploiting the variation on the interference levels from multiple interferers, efficient clustering algorithms are proposed such that clusters formed can capture strong interference as intracluster interference, leaving relatively weak interference as intercluster interference. Then, the intercluster interference can be coarsely modeled as noise. We also consider the precoder/equalizer design in a clustered system and show the importance of incorporating the aggregated intercluster interference in the design. Simulation results show that proper clustering combined with generalized IA precoder/equalizer design leads to significant gains on the achievable sum rate.

Design and measurement-based evaluations of coherent JT CoMP: a study of precoding, user grouping and resource allocation using predicted CSI

Coordinated multipoint (CoMP) transmission provides high theoretic gains in spectral efficiency with coherent joint transmission (JT) to multiple users. However, this requires accurate channel state information at the transmitter (CSIT) and also user groups with spatially compatible users. The aim of this paper is to use measured channels to investigate if significant CoMP gains can still be obtained with channel estimation errors. This turns out to be the case, but requires the combination of several techniques. We here focus on coherent downlink JT CoMP to multiple users within a cluster of cooperating base stations. The use of Kalman predictors is investigated to estimate the complex channel gains at the moment of transmission. It is shown that this can provide sufficient CSIT quality for JT CoMP even for long (>20 ms) system delays at 2.66 GHz at pedestrian velocities or, for lower delays, at 500 MHz, at vehicular velocities. A user grouping and resource allocation scheme that provides appropriate groups for CoMP is also suggested. It provides performance close to that obtained by exhaustive search at very low complexity, low feedback cost and very low backhaul cost. Finally, a robust linear precoder that takes channel uncertainties into account when designing the precoding matrix is considered. We show that, in challenging scenarios, this provides large gains compared with zero-forcing precoding. Evaluations of these design elements are based on measured channels with realistic noise and intercluster interference assumptions. These show that high JT CoMP gains can be expected, on average over large sets of user positions, when the above techniques are combined - especially in severely intracluster interference limited scenarios.

Joint precoding selection diversity with limited feedback

Coordinated multiple-point transmission (CoMP) is one of important techniques for the reduction of inter-cluster interference. Three major schemes have been presented for CoMP-joint processing transmission (CoMP-JPT) under limited-feedback environments: global, local, and single-frequency network precoding methods. However, most previous studies have demonstrated effectiveness only in specific environments without presenting numerical analyses. In this paper, we verify the characteristics of each precoding scheme based on zero-forcing beamforming (ZFBF) with semi-orthogonal user selection (SUS) by exploiting numerical analysis. In addition, we propose a selection algorithm that achieves the diversity of the precoding schemes based on limited feedback according to the downlink channel status of cellular systems. In addition, for the 3rd Generation Partnership Project Long Term Evolution-Advanced (3GPP LTE-Advanced), a network protocol that is required to adapt the CoMP-JPT scheme is implemented. Through simulations, we demonstrate that the proposed system can effectively improve the quality of service for cell-edge users while guaranteeing fairness compared to the conventional precoding schemes.

Optimal Antenna Cluster Size in Cell-Free Distributed Large-Scale Antenna Systems with Imperfect CSI and Inter-Cluster Interference

In cell-free large-scale distributed antenna systems (L-DASs), the antennas are distributed over the intended coverage area. Introducing cooperation among the antennas can significantly improve the system throughput. However, only finite-cluster-size (limited) cooperation with L-DAS antenna clusters is realistic due to practical limitations. In this paper, the impact of antenna cluster size on the downlink sum rate of frequency-division duplex (FDD) cell-free L-DASs is analyzed, considering imperfect channel state information (CSI) and intercluster interference (ICLI). We investigate the optimal cluster size in terms of maximizing the downlink sum rate with respect to the overhead of imperfect channel training and feedback. When the number of users is sufficiently large, closed-form lower bounds of the ergodic sum capacity, which are leveraged to analyze the system performance, are derived by constructing different rate-achieving user-scheduling schemes. Both analog and digital feedback schemes are considered to evaluate the imperfect channel feedback. Based on these, closed-form expressions of the optimal cluster size for 1-D antenna topology systems and the corresponding achievable rates are derived. The scaling law of the optimal cluster size for 2-D antenna topology systems is also given. Numerical results demonstrate the impact of the signal-to-noise ratio (SNR) and the block length on the achievable rates and the optimal cluster size, which agree with our analytical results.

MIMO Interference Alignment in Random Access Networks

In this paper, we analyze a multiple-input multiple-output (MIMO) interference channel where nodes are randomly distributed on a plane as a spatial Poisson cluster point process. A Poisson cluster point process consists of clusters with fixed number of points randomly distributed as with the cluster centers distributed randomly on the plane. The nodes in each cluster use interference alignment (IA) to suppress intra-cluster interference but unlike most work on IA, we do not neglect inter-cluster interference. We also connect the accuracy of channel state information to the distance between the nodes, i.e., the quality of CSI degrades with increasing distance. Accounting for the training and feedback overhead, we derive the transmission capacity of this MIMO IA ad hoc network and then compare it to open-loop (interference-blind) spatial multiplexing. Finally, we present exemplary system setups where spatial multiplexing outperforms IA due to the imperfect channel state information or the non-aligned inter-cluster interference.

On the Capacity of Cluster-Based Cooperative MIMO Cellular System with Universal or Fractional Frequency Reuse

The information-theoretic capacity for the cluster-based multicell cooperative processing (MCP) network with inter-cluster interference is investigated in this paper. An upper bound for the ergodic capacity is derived by the QR decomposition of the channel matrix, which is concisely expressed and close to the results from numerical simulations. Capacity results for the universal frequency reuse (UFR) network show that the cluster-based MCP system has great advantages over the non-cooperated system, and the capacity gain depends mainly on the size of the cooperative cluster, the radius of the cell and the path loss exponent (PLE). However, the cluster-based UFR system is still interference limited, whose capacity declines sharply due to the inter-cluster interference. Therefore, a cluster-based fractional frequency reuse (FFR) network is proposed to improve the system capacity, simulation results show that the cluster-based FFR system can outperform the UFR system, especially for the cases of small radius of cell or small PLE.

Resource allocation for clustered network MIMO OFDMA systems

In this article, we address the resource allocation problem for the downlink of a large network multiple input multiple output orthogonal frequency division multiplexing system with 3-sector base stations. The system is statically divided into a number of disjoint clusters of sectors. A two-step resource allocation scheme is proposed involving the inter-cluster and the intra-cluster levels. As a first step or inter-cluster level, two cooperative frequency reuse approaches are designed to mitigate the inter-cluster interference. A user partition method is proposed to divide the users of each cluster into cluster-edge and cluster-center users. To balance the cell-edge and the cell-average performance, a fairness jug function is introduced to determine the frequency partition of the cooperative frequency reuse approaches. Then, as a second step or intra-cluster level, a utility-based joint scheduling and power allocation algorithm is proposed for each cluster, to maximize the sum utility of all users in the cluster under per-sector power constraints. Zero-forcing joint transmission is used across multiple sectors within the same cluster. Simulation results show that the proposed scheme can efficiently reduce the inter-cluster interference and provide considerable performance improvement in terms of both the cell-edge and cell-average user data rate. The proposed two-step resource allocation scheme can be implemented independently in each cluster without inter-cluster information exchange, which is an attractive property for practical systems, since it reduces both the network signaling overhead and the computational complexity.

Interference mitigation techniques for clustered multicell joint decoding systems

Multicell joint processing has originated from information-theoretic principles as a means of reaching the fundamental capacity limits of cellular networks. However, global multicell joint decoding is highly complex and in practice clusters of cooperating Base Stations constitute a more realistic scenario. In this direction, the mitigation of intercluster interference rises as a critical factor towards achieving the promised throughput gains. In this paper, two intercluster interference mitigation techniques are investigated and compared, namely interference alignment and resource division multiple access. The cases of global multicell joint processing and cochannel interference allowance are also considered as an upper and lower bound to the interference alignment scheme, respectively. Each case is modelled and analyzed using the per-cell ergodic sum-rate throughput as a figure of merit. In this process, the asymptotic eigenvalue distribution of the channel covariance matrices is analytically derived based on free-probabilistic arguments in order to quantify the sum-rate throughput. Using numerical results, it is established that resource division multiple access is preferable for dense cellular systems, while cochannel interference allowance is advantageous for highly sparse cellular systems. Interference alignment provides superior performance for average to sparse cellular systems on the expense of higher complexity.