MIMO HetNets Research Articles

Enhancing Downlink Transmission in MIMO HetNet With Wireless Backhaul

We propose a transmission scheme that exploits the spatial degrees of freedom from large antenna arrays to maximize the downlink sum-rate of user equipment (UE) in a heterogeneous network. Our scheme incorporates the design of 1) a new precoder for the millimeter wave (mmWave) wireless backhaul; and 2) an enhanced small cell range expansion method for data link transmission. Aside from the advantage of lower implementation and computational complexity, the wireless backhaul precoder can simultaneously support multiple small access points with multi-streams. Under the constraint of wireless backhaul capacity, a downlink cooperation precoding algorithm is proposed to suppress the interference caused by small cell range expansion. Simulation results show that the proposed precoder in backhaul link can use a small number of radio frequency (RF) chains to achieve the sum-rate performance that approaches the one under traditional block diagonalization precoder, which requires the number of the RF chains to be comparable with that of antenna elements. Moreover, we give a lower bound for the overall UE sum-rate of the downlink cooperation precoding algorithm.

Spectral and Energy Efficient Resource Allocation for Massive MIMO HetNets With Wireless Backhaul

This letter provides a spectral and energy efficiency evaluation framework for massive MIMO heterogeneous networks with wireless backhaul. This framework is to maximize the weighted summation of spectral efficiency and energy efficiency with guaranteeing quality of service for users, interference mitigation, and sufficient capacity in wireless backhaul. To solve this non-convex problem, we develop a novel alternating optimization algorithm, which is a combination of Lagrange dual with successive convex approximation. Numerical results verify the effectiveness of the framework in improving the energy and spectral efficiency by comparing with the other schemes.

Coverage Analysis of Multi-Stream MIMO HetNets With MRC Receivers

Most of the current research on the coverage performance of multi-stream MIMO heterogeneous networks (HetNets) has focused on a single data-stream. This does not always provide accurate results as our analysis show the cross-stream correlation due to interference can greatly affect the coverage performance. This paper analyzes the coverage probability in such systems, and studies the impact of cross-stream correlation. Specifically, we focus on the max-SIR cell association policy and leverage stochastic geometry to study scenarios, whereby a receiver is considered in the coverage, if all of its data-streams are successfully decodeable. Assuming open-loop maximum ratio combining (MRC) at receivers, we consider the cases where partial channel state information is available at the receiver. We then obtain an upper-bound on the coverage and formulate cross-stream SIR correlation. We further show that approximating such systems based on fully-correlated (non-correlated) data-streams results in a slight underestimation (substantial overestimation) of the coverage performance. Our results provide insights on the multiplexing regimes where densification improves the coverage performance and spectral efficiency. We also compare MRC with more complex zero-forcing receiver and provide quantitative insights on the design tradeoffs. Our analysis is validated via extensive simulations.

MIMO HetNet IEEE 802.11p–LTE deployment in a vehicular urban environment

Intelligent Transportation Systems (ITS) are receiving significant interest due to a wide variety of applications such as road safety, traffic efficiency and infotainment. To satisfy the diverse vehicular application requirements, this paper presents a detailed comparative performance simulation study over IEEE 802.11p, LTE and the proposed Heterogeneous (HetNet) IEEE 802.11p–LTE network for urban environments. Therefore, a hybrid handover algorithm is proposed, combining the IEEE 802.11p-based multihop clustering and the Long-Term Evolution (LTE) networks, with the goal of achieving a high data packet delivery ratio (PDR) and low delay. The COST-231 Walfisch–Ikegami propagation model is evaluated, incorporating 3D antenna radiation patterns measured in an Anechoic Chamber. The performance evaluation analysis is validated through VEINS–OMNeT++ network simulator over several performance metrics such as Throughput, Packet Delivery Ratio, End-to-End Delay and SNIR Lost Packets for a variety of vehicle density and vehicle speed under both SISO and MIMO open loop 2×2 Spatial Multiplexing (SM) scheme antenna techniques respectively. The results indicate that the HetNet 802.11p–LTE network is the most prominent solution in urban environments outperforming both IEEE 802.11p and LTE in terms of delay, reliability, and scalability, whereas LTE offers acceptable performance for sparse network topologies.

Joint Design of User Association and Power Allocation With Proportional Fairness in Massive MIMO HetNets

Although the massive MIMO enabled heterogeneous networks (HetNets) can intensify the spectral efficiency benefits, the proper user association and resource allocation are both crucial to achieve desirable performance since the power consumption of base station (BS) scales with the large number of antennas. This paper aims to investigate joint design of user association and power allocation with loads constraint and transmit power constraint for the massive MIMO HetNets by considering proportional fairness about the spectral efficiency under imperfect channel state information. First, we derive a closed-form lower bound on the ergodic spectral efficiency with linear zero-forcing beamforming, based on which, a mixed-integer nonlinear programming problem is formulated. It is difficult to efficiently obtain an exact solution since it is non-convex and combinational. To solve this NP-hard problem, an effective algorithm with guaranteed convergence is proposed, where the original problem is decomposed into the corresponding subproblems, which can be solved by low complexity approaches, respectively. Numerical results show that how the number of antennas and the number of BSs affect the spectral efficiency, and our proposed algorithm outperforms other algorithms in terms of the spectral efficiency and load balancing.

User Association and Interference Management in Massive MIMO HetNets

Two key traits of 5G cellular networks are much higher base station (BS) densities—especially in the case of low-power BSs—and the use of massive MIMO at these BSs. This paper explores how massive MIMO can be used to jointly maximize the offloading gains and minimize the interference challenges arising from adding small cells. We consider two interference management approaches: joint transmission (JT) with local precoding, where users are served simultaneously by multiple BSs without requiring channel state information exchanges among cooperating BSs, and resource blanking, where some macro BS resources are left blank to reduce the interference in the small cell downlink. A key advantage offered by massive MIMO is channel hardening, which enables to predict instantaneous rates a priori . This allows us to develop a unified framework, where resource allocation is cast as a network utility maximization (NUM) problem, and to demonstrate large gains in cell-edge rates based on the NUM solution. We propose an efficient dual subgradient based algorithm, which converges towards the NUM solution. A scheduling scheme is also proposed to approach the NUM solution. Simulations illustrate more than 2x rate gain for 10th percentile users vs. an optimal association without interference management.

Success Probability and Area Spectral Efficiency in Multiuser MIMO HetNets

We derive a general and closed-form result for the success probability in downlink multiple-antenna (MIMO) heterogeneous cellular networks (HetNets), utilizing a novel Toeplitz matrix representation. This main result, which is equivalently the signal-to-interference ratio (SIR) distribution, includes multiuser MIMO, single-user MIMO and per-tier biasing for K different tiers of randomly placed base stations (BSs), assuming zero-forcing precoding and perfect channel state information. The large SIR limit of this result admits a simple closed form that is accurate at moderate SIRs, e.g., above 5 dB. These results reveal that the SIR-invariance property of SISO HetNets does not hold for MIMO HetNets; instead the success probability may decrease as the network density increases. We prove that the maximum success probability is achieved by activating only one tier of BSs, while the maximum area spectral efficiency (ASE) is achieved by activating all the BSs. This reveals a unique tradeoff between the ASE and link reliability in multiuser MIMO HetNets. To achieve the maximum ASE while guaranteeing a certain link reliability, we develop efficient algorithms to find the optimal BS densities. It is shown that as the link reliability requirement increases, more BSs and more tiers should be deactivated.

User Association in Massive MIMO HetNets

Massive MIMO and small cell are both recognized as the key technologies for the future 5G wireless systems. In this paper, we investigate the problem of user association in a heterogeneous network (HetNet) with massive MIMO and small cells, where the macro base station (BS) is equipped with a massive MIMO and the picocell BS's are equipped with regular MIMOs. We first develop centralized user association algorithms with proven optimality, considering various objectives such as rate maximization, proportional fairness, and joint user association and resource allocation. We then model the massive MIMO HetNet as a repeated game, which leads to distributed user association algorithms with proven convergence to the Nash Equilibrium (NE). We demonstrate the efficacy of these optimal schemes by comparison with several greedy algorithms through simulations.

Iterative Equalization and Interference Alignment for Multiuser MIMO HetNets with Imperfect CSI

In this paper we consider a scenario, where several small-cells work under the same coverage area and spectrum of a macrocell. The signals stemming from the small-cell (macrocell) users if not carefully dealt with will generate harmful interference into the macrocell (small-cell). To tackle this problem interference alignment and iterative equalization techniques are considered. By using IA all interference generated by the small-cell (macrocell) users is aligned along a low dimensional subspace, at the macrocell (small-cells). This reduces considerably the amount of resources allocated, to enable the coexistence of the two systems. However, perfect IA requires the availability of error-free channel state information (CSI) at the transmitters. Due to CSI errors one can have substantial performance degradation due to imperfect alignments. Since in this work the IA precoders are based on imperfect CSI, an efficient iterative space-frequency equalization is designed at the receiver side to cope with the residual aligned interference. The results demonstrate that iterative equalization is robust to imperfect CSI and removes efficiently the interference generated by the poorly aligned interference. Close to matched filter bound performance is achieved, with a very few number of iterations.

Downlink MIMO HetNets: Modeling, Ordering Results and Performance Analysis

We develop a general downlink model for multi-antenna heterogeneous cellular networks (HetNets), where base stations (BSs) across tiers may differ in terms of transmit power, target signal-to-interference-ratio (SIR), deployment density, number of transmit antennas and the type of multi-antenna transmission. In particular, we consider and compare space division multiple access (SDMA), single user beamforming (SU-BF), and baseline single-input single-output (SISO) transmission. For this general model, the main contributions are: (i) ordering results for both coverage probability and per user rate in closed form for any BS distribution for the three considered techniques, using novel tools from stochastic orders, (ii) upper bounds on the coverage probability assuming a Poisson BS distribution, and (iii) a comparison of the area spectral efficiency (ASE). The analysis concretely demonstrates, for example, that for a given total number of transmit antennas in the network, it is preferable to spread them across many single-antenna BSs vs. fewer multi-antenna BSs. Another observation is that SU-BF provides higher coverage and per user data rate than SDMA, but SDMA is in some cases better in terms of ASE.