Non-ideal Backhaul Research Articles

Coordinated multipoint in dense heterogeneous networks with overlapping microcell expanded regions and its effect on backhaul links

One of the goals of Heterogeneous Networks (HetNets) is to offload traffic from the macrocell BS to the microcell base stations (BSs). It has been proposed that in order for the microcell to acquire more users and offload increasing amounts of traffic, its region of coverage must be expanded. This however causes significant cross-tier interference, which can be remedied by utilizing coordinated multipoint (CoMP) within the microcell expanded region (ER). Our methodology considers the effect of overlapping ERs, and proposes the cooperation of concerned microcell BSs with the macrocell BS to further reduce the outage probability and improve throughput. Another important consideration in our analysis is the effect of having non-ideal backhaul on the system’s performance. That is, CoMP increases the strain on the backhaul network, since additional data that is proportional to the number of cooperating BSs needs to travel on the backhaul links. Furthermore, the delay should be minimal and less than one subframe duration in order for reported channel state information to remain valid. With this in mind, our proposed system considers the effect of having non-ideal backhaul in a cellular network with CoMP, while taking into account overlaps in the microcell ERs.

Flexible Coverage for Backhaul-Limited Ultradense Heterogeneous Networks: Throughput Analysis and $\eta$-Optimal Biasing

In fifth-generation ultradense heterogeneous network, backhaul plays an important role to provide connection to core networks for small base stations (SBSs). With the densification, nonideal backhaul will be deployed extensively, which constrains the throughput improvement due to the limited backhaul capacity. This paper models the SBSs and users as independent Poisson point processes and derives a semi-closed-form expression that analyzes the ergodic throughput of the network where SBSs have limited backhaul capacity. Based on analysis, to accomplish flexible coverage with limited backhaul, an optimization problem is formulated which accounts for cell association and aims at maximizing the number of offloading users while simultaneously minimizing the biasing factors and guaranteeing the received signal-to-interference-and-noise ratio of users when offloading. The optimization problem is shown to be a mixed-integer nonlinear problem, which can obtain a suboptimal solution by convex relaxation and further a distributed solution by problem decomposition via primal-dual method. Considering the complexity of ultradense network and practical implementation, a backhaulaware η-optimal biasing adjustment model is proposed for flexible coverage. This model aims to optimize the coverage for throughput improvement while matching the backhaul capacity. The simulation results show that average user and SBS throughput can be improved significantly by 2× when backhaul is constrained. Due to the transmit power and interference constraints on access link, there is no need to allocate too much bandwidth to backhaul, which provides guidance for self-backhaul resource allocation.

Coordinated beamforming for heterogeneous small‐cell networks with a non‐ideal backhaul

In this article, intra- and inter-cell interference caused by the non-ideal backhaul in coordinated multipoint (CoMP) are studied. A recursive estimation-based zero-forcing beamforming (RE-ZFBF) scheme is proposed to mitigate the interference. Based on an initial value, the RE-ZFBF scheme recursively approximates the beamformer variation between two consecutive time points by exploiting the temporal channel correlation. In contrast to a previous work, the authors convert the original non-convex constraint quality-of-service problem to an unconstrained convex one, by optimising the estimation of the beamformer error, rather than the beamforming power. It is shown that the proposed scheme can mitigate at most half the intra- and inter-cell interference, enhance the ZFBF performance, and outperform the existing works for CoMP with a non-ideal backhaul in heterogeneous small-cell networks.

Energy Efficiency in Latency-Constrained Application Offloading From Mobile Clients to Multiple Virtual Machines

This paper addresses the energy-latency tradeoff in distributed application offloading, in which an energy-limited handset offloads totally or partially an application to one or several virtual machines (VMs) located in remote locations or access points (APs) close to the mobile terminal (MT). One of the APs (the serving AP) provides radio access to the MT and is connected to the VMs through nonideal backhaul (BH) links. In this setting, we optimize the offloading strategy (including the joint optimization of radio and computational resources) to minimize the energy consumption at the MT subject to a maximum latency constraint. In addition, we propose robust designs to cope with imperfect acquisition of the channel state information (CSI) and the BH parameters. Our findings show that as far as the energy-latency tradeoff is concerned, the optimal order of activation of the VMs does not depend on their processing capabilities but the delays of the BH links. However, once a VM is selected to participate in the processing, the optimal amount of processing allocated to such VM depends on its computational capabilities as well as on the features (capacity and delay) of the BH link. Additionally, offloading decisions become more conservative as the uncertainty in CSI and BH parameters increases.

Decoupled Access in HetNets With Backhaul Constrained Small Base Stations

This paper investigates the uplink (UL) and downlink decoupled access in heterogeneous networks with backhaul constraints. A capacity-based user association policy is proposed for users with decoupled access, where small base stations (SBSs) connect to macro base stations via non-ideal backhaul. The UL association probabilities are derived under this policy, where the limitations of association probabilities are obtained when the density of SBSs grows to infinity. Then, the UL signal-to-interference-plus-noise ratio (SINR) coverage probabilities are derived and analyzed for different SINR thresholds. According to the analysis, the effects of the limited backhaul capacity on the average UL SINR coverage probabilities are presented, where a jump discontinuity, which can be considered as a certain SINR threshold, is shown to be brought by the backhaul capacity constraint. It is demonstrated that denser deployment of SBSs helps improve UL performance significantly for users with SINR lower than such SINR threshold while hardly benefits those with SINR higher than it. Finally, the theoretical results are validated via simulations.

Coverage and Association Bias Analysis for Backhaul Constrained HetNets with eICIC and CRE

Heterogeneous networks (HetNets) are envisioned as a key solution to address the ever increasing capacity demand in wireless networks. With the deployment of enhanced radio access technologies, the non-ideal backhaul will become a potential network bottleneck. However, the impact of backhaul capacities (BCs) on the network coverage and offloading are not well understood. To address these issues, using tools from stochastic geometry, we propose a tractable framework for analyzing the impact of BCs on the network coverage and the optimal offloading bias in HetNets with cell range expansion (CRE) and time domain enhanced inter-cell interference coordination (eICIC) techniques. Conditioned on guaranteeing the minimum quality of service (QoS) of serving users, the coverage probability is derived as a function of offloading bias and BC parameters. We show how non-ideal backhaul alters the network coverage and the optimal bias. Compared with the perfect backhaul case, the optimal coverage and the optimal bias exhibit different behaviors in the case of limited BC.

Analysis of K-tier 5G heterogeneous cellular network with dual-connectivity and uplink–downlink decoupled access

Smallcells deployment in heterogeneous networks (HetNets) introduce uplink (UL) downlink (DL) asymmetry, backhaul bottleneck, cell load imbalances, increased core network signaling, interference and mobility management problems. In order to address these issues, concept of dual connectivity has been introduced in 3rd generation partnership project (3GPP) release 12. In dual connectivity, a given user equipment can consume radio resources of at least two different network points connected through non-ideal backhaul for spectrum aggregation and cooperative access mechanisms in dense 5G HetNets. Alternatively, another concept of downlink and uplink decoupling (DUDe) has also been recently introduced in 3GPP to improve uplink performance, load balancing and cell capacity. In order to take advantage of the strengths of these latest developments, this paper significantly advances prior work by analyzing K-tier 5G HetNets having dual connectivity and decoupled access (joint DUDe dual-connectivity) for spectrum aggregation in UL and DL. In the preceding works, K-tiers as per present-day heterogeneity, uplink power control and receiver noise have not been considered for joint DUDe dual-connectivity. With the use of stochastic geometry, we have developed closed form solutions for association, coverage and outage probabilities along with average throughput for joint DUDe dual-connectivity by considering uplink power control, receiver noise and K-tiers of HetNets. The resultant performance metrics are evaluated in terms of achieved gains over conventional downlink received power access policies. Results show that cell association technique based on joint DUDe dual-connectivity can significantly improve load balancing, mobility management and UL performance for forthcoming 5G HetNets.

Dual connectivity for LTE small cell evolution: functionality and performance aspects

DC is one of the most important features introduced in Release 12 of the 3GPP specifications. DC aims at increasing the per-user throughput by improving the utilization of radio resources across two base stations connected via non-ideal backhaul (X2) and operating on different carrier frequencies. By making it possible to maintain the connection to the primary cell located in the macro base station while accessing the extra capacity provided by the small cell layer, DC can also improve the mobility performance in small cell deployments. This article gives an overview of the DC feature as standardized in Release 12. We summarize the supported scenarios and the DC functionality, and also demonstrate by means of detailed system-level simulations how DC can improve end-user throughput and mobility performance.

Proportional Fair Traffic Splitting and Aggregation in Heterogeneous Wireless Networks

Traffic load balancing and resource allocation is set to play a crucial role in leveraging the dense and increasingly heterogeneous deployment of multiradio wireless networks. Traffic aggregation across different access points (APs)/radio access technologies (RATs) has become an important feature of recently introduced cellular standards on LTE dual connectivity and LTE-WLAN aggregation (LWA). Low complexity traffic splitting solutions for scenarios where the APs are not necessarily collocated are of great interest for operators. In this letter, we consider a scenario, where traffic for each user may be split across macrocell and an LTE or WiFi small cells connected by nonideal backhaul links, and develop a closed form solution for optimal aggregation accounting for the backhaul delay. The optimal solution lends itself to a “water-filling” based interpretation, where the fraction of user’s traffic sent over macrocell is proportional to ratio of user’s peak capacity on that macrocell and its throughput on the small cell. Using comprehensive system level simulations, the developed optimal solution is shown to provide substantial edge and median throughput gain over algorithms representative of current 3GPP-WLAN interworking solutions. The achievable performance benefits hold promise for operators expecting to introduce aggregation solutions with their existing WLAN deployments.

Green HetNet CoMP: Energy Efficiency Analysis and Optimization

This paper investigates advanced energy-efficient wireless systems in orthogonal frequency-division multiple access (OFDMA) downlink networks using coordinated multipoint (CoMP) transmissions between the base stations (BSs) in a heterogeneous network (HetNet), which is adopted by Third-Generation Partnership Project (3GPP) Long-Term Evolution (LTE)-Advanced to meet International Mobile Telecommunications-Advanced targets. HetNet CoMP has received significant attention as a way of achieving spectral efficiency (SE) and energy efficiency (EE). Usually, in the literature, the total network power consumption is restricted to the sum of the power consumption of all BSs. The significance of the power consumption of the backhaul links in wireless networks is normally omitted for its trivial effect with respect to that of the radio BSs. For SE and EE analysis of HetNet CoMP, the energy and bandwidth consumption of the backhaul is considered, without which, the investigation remains incomplete. However, SE and EE are design criteria in conflict with each other, and a careful study of their tradeoff is mandatory for designing future wireless communication systems. The EE is measured as “throughput (bits) per joule,” whereas the power consumption model includes RF transmit (radiated), circuit, and backhaul power. Furthermore, a nonideal backhaul model such as a microwave link is also investigated within intra-HetNet-CoMP (inside one cell), where an implementing fiber is not feasible. An intercell interference (ICI) coordination method is also studied to mitigate ICI. At the end, a novel resource allocation algorithm is proposed—modeled as an optimization problem—which takes into account the total power consumption, including radiated, circuit, and backhaul power, and the minimum required data rate to maximize EE. Given an SE requirement, the EE optimization problem is formulated as a constrained optimization problem. The considered optimization problem is transformed into a convex optimization problem by redefining the constraint using cubic inequality, which results in an efficient iterative resource allocation algorithm. In each iteration, the transformed problem is solved by using dual decomposition with a projected gradient method. Simulations results demonstrate how backhaul has a significant impact on total power consumption and the effectiveness of the studied schemes. In addition, the results demonstrate that the proposed iterative resource allocation algorithm converges within a small number of iterations and illustrate the fundamental tradeoffs between SE and EE. Our analytical results shed light on future “green” network planning in advanced OFDMA wireless systems like those envisioned for a fifth-generation (5G) system.

Distributed Power Allocations in Heterogeneous Networks With Dual Connectivity Using Backhaul State Information

Long Term Evolution (LTE) release 12 proposes the use of dual connectivity in heterogeneous cellular networks, where a user equipment (UE) maintains parallel connections to a macrocell base station and to a low-tier node such as a picocell base station or relay. In this paper, we propose distributed multi-objective power control where each UE independently adapts its transmit power on its dual connections, where the uplinks could be of unequal bandwidth and have non-ideal backhaul links. In the proposed optimization, the UEs dynamically switch between data rate maximization and transmit power minimization as the backhaul load varies. To address the coupling between interference and the backhaul load, we propose a low-overhead convergence mechanism which does not require explicit coordination between UEs and also derive a closed-form expression of the transmit power levels at equilibrium. Simulation results show that our scheme achieves higher aggregate end-to-end data rate and significant power saving in comparison to a scheme that employs a greedy algorithm and a scheme that employs only waterfilling.

Opportunistic Hybrid ARQ—Enabler of Centralized-RAN Over Nonideal Backhaul

Centralized radio access networks rely on transport networks with very high throughput and very low latency. In the case of nonideal backhaul, it may be necessary to only centralize parts of the radio access network. This implies several timing and protocol constraints, e.g., predefined timing of retransmissions due to hybrid ARQ. In this paper, an opportunistic hybrid-ARQ approach is introduced, which estimates the decoding error probability at the radio access points and directly provides feedback to mobile terminals, while actual decoding is performed at the central processor. Furthermore, an effective signal-to-noise ratio (SNR) is derived, which allows for the use of a single mapping curve.

Non-Ideal Backhaul Based Spectrum Splitting and Power Allocation for Downlink <roman>CoMP</roman> in Cognitive Macro/Femtocell Networks

This letter propose a novel scheme for cognitive macro/femtocell downlink coordinated multipoint (CoMP) transmission to improve the capacity of femtocell without affecting the normal communications of macrocell users (MUs). In specific, the femtocell access point (FAP) assists the macrocell base station (MBS) by jointly transmiting to the MU in the vicinity of the femtocell. A portion of the spectrum originally assigned to the MU is reserved for CoMP. In return, the rest can be freely utilized by the femtocell. Moreover, the impact of non-ideal backhaul (NIB) is considered, which makes the joint spectrum splitting and power allocation non-convex. A universal dual bisection algorithm is proposed to achieve the globally optimal solution. Simulation results indicate that the capacity of femtocell is enhanced up to 200% relative to the traditional methods. Meanwhile, the data communications of MUs are well protected compared with the scheme that ignores the impact of NIB.