Downlink Inter-cell Interference Research Articles

Further Research on Frequency Allocation (19-Cell System) Method based on IFR and FFR

Many of the most advanced technology has a basic need for efficient telecommunication. In order to achieve this goal, the team should allocate those frequency channels in an intelligent way so that the interference can be reduced to the maximum extent. Here the team introduced a new method based on IFR3&IFR1 (Integer frequency reuse) in a 19-cell network, but also apply the FFR (fractional frequency reuse) method to reduce the interference ulteriorly. In the pure IFR situation, the integer frequency reuse factor and the cellular network specification collectively decide the network capacity. While in FFR only a fraction of the whole bandwidth is used by the users in the edge. By contrast, the users near the BS can make use of the total bandwidth. The cell is divided into an outer and an inner part in this effective way. Fractional Frequency Reuse (FFR) and its derivative method are accepted widely in the downlink (DL) inter-cell interference coordination(ICIC) schemes. The team also optimized the FFR method by measuring the distance in a more precise way. The team utilized Matlab to make a simulation of the system applying the new method and come to a couple of reasonable conclusions by comparing the FFR+IFR3 with FFR+IFR3. FFR+IFR3 has a better performance against FFR+IFR1 in a system whose distance between each cell is with more accuracy. While the average number of users per cell and transmission power for cell edge have little impact on average capacity. When the SNR increases, the network capacity starts steep but later flattens. Our method is more intelligent and can minish interference efficiently.

Graph Theory Based Beam Scheduling for Inter-Cell Interference Avoidance in MmWave Cellular Networks

The application of high directional beam in millimeter wave leads to a new downlink inter-cell interference (ICI) characteristic that the ICI is high only if the beam of a neighboring cell points towards a user in local cell. This characteristic indicates that the ICI can be avoided if the beams in the network are scheduled coordinately. In this paper, we investigate the time-domain beam scheduling problem for downlink ICI avoidance by modeling the entire network as a graph, where the number of time slots occupied by each beam is considered as a constraint to guarantee service quality. The beams in each cell are classified according to the neighboring cells they may interfere with. If two adjacent cells simultaneously use the beam which may interfere with each other, beam collision occurs, leading to strong ICI. Based on graph theory, we propose a least beam collision (LBC) algorithm to minimize the number of beam collisions, and we prove that this LBC algorithm is capable of acquiring the global minimum beam collision solution. Our simulation results verify that the strong ICI between two neighboring cells can be efficiently eliminated, which benefits the transmission reliability and the network's sum rate.

Reinforcement Learning-Based Downlink Interference Control for Ultra-Dense Small Cells

The dense deployment of small cells in 5G cellular networks raises the issue of controlling downlink inter-cell interference under time-varying channel states. In this paper, we propose a reinforcement learning based power control scheme to suppress downlink inter-cell interference and save energy for ultra-dense small cells. This scheme enables base stations to schedule the downlink transmit power without knowing the interference distribution and the channel states of the neighboring small cells. A deep reinforcement learning based interference control algorithm is designed to further accelerate learning for ultra-dense small cells with a large number of active users. Analytical convergence performance bounds including throughput, energy consumption, inter-cell interference, and the utility of base stations are provided and the computational complexity of our proposed scheme is discussed. Simulation results show that this scheme optimizes the downlink interference control performance after sufficient power control instances and significantly increases the network throughput with less energy consumption compared with a benchmark scheme.

Multi-Cell Cooperative Scheduling for Network Utility Maximization With User Equipment Side Interference Cancellation

Downlink inter-cell interference is a major limiting factor in current cellular systems. Several trends exacerbate the interference problem: cells become denser, more heterogeneous, and are more randomly deployed. To tackle this problem, there are many pure network-side solutions proposed, e.g., eICIC and feICIC in 3GPP LTE. However, these solutions are less spectrally efficient because the interferer usually needs to mute or reduce power to keep its interference power to victims below a tolerable level. In this paper, we consider an alternative solution in which the user equipment may perform interference cancellation (IC). In theory, this is a more spectrally efficient scheme as compared with the pure network-side solutions. In practice, however, to fully exploit the benefit of IC, the network should adopt some IC-aware scheduling rules. We propose a multi-cell joint scheduling, joint rate selection and power allocation problem in an IC-enabled network, trying to maximize the network utility. To make our solutions practical and readily deployable, we consider different settings. We explore both theoretically optimal IC scheme and the more practical symbol-level IC. On the other hand, we propose both dynamic and semi-static solutions, and compare them. Our simulation results show that while the average throughput increases by only around 10%, cell edge users can gain more than 50%.

How to Ensure Reliable Connectivity for Aerial Vehicles Over Cellular Networks

Widely deployed cellular networks are an attractive solution to provide large scale radio connectivity to unmanned aerial vehicles. One main prerequisite is that co-existence and optimal performance for both aerial and terrestrial users can be provided. Today's cellular networks are, however, not designed for aerial coverage, and deployments are primarily optimized to provide good service for terrestrial users. These considerations, in combination with the strict regulatory requirements, lead to extensive research and standardization efforts to ensure that the current cellular networks can enable reliable operation of aerial vehicles in various deployment scenarios. In this paper, we investigate the performance of aerial radio connectivity in a typical rural area network deployment using extensive channel measurements and system simulations. First, we highlight that downlink and uplink radio interference play a key role, and yield relatively poor performance for the aerial traffic, when load is high in the network. Second, we analyze two potential terminal side interference mitigation solutions: interference cancellation and antenna beam selection. We show that each of these can improve the overall, aerial and terrestrial, system performance to a certain degree, with up to 30% throughput gain, and an increase in the reliability of the aerial radio connectivity to over 99%. Further, we introduce and evaluate a novel downlink inter-cell interference coordination mechanism applied to the aerial command and control traffic. Our proposed coordination mechanism is shown to provide the required aerial downlink performance at the cost of 10% capacity degradation in the serving and interfering cells.

Multi-Layer Precoding: A Potential Solution for Full-Dimensional Massive MIMO Systems

Massive MIMO systems achieve high sum spectral efficiency by simultaneously serving large numbers of users. In time division duplexing systems, however, the reuse of uplink training pilots among cells results in channel estimation errors, which causes downlink inter-cell interference. Handling this interference is challenging due to the large channel dimensionality and the high complexity associated with implementing large precoding/combining matrices. In this paper, we propose multi-layer precoding to enable efficient and low-complexity operation in full-dimensional massive MIMO, where a large number of antennas are used in two dimensions. In multi-layer precoding, the precoding matrix of each base station is written as a product of a number of precoding matrices. Multi-layer precoding: 1) leverages the directional characteristics of large-scale MIMO channels to manage inter-cell interference with low channel knowledge requirements and 2) allows for an efficient implementation using hybrid analog/digital architectures. We present and analyze a specific multi-layer precoding design for full-dimensional massive MIMO systems. The asymptotic optimality of the proposed design is then proved for some special yet important channels. Numerical simulations verify the analytical results and illustrate the potential gains of multi-layer precoding compared with other multi-cell precoding solutions.

Opportunistic Downlink Interference Alignment for Multi-Cell MIMO Networks

In this paper, we propose an opportunistic downlink interference alignment (ODIA) for interference-limited cellular downlink, which intelligently combines user scheduling and downlink IA techniques. The proposed ODIA not only efficiently reduces the effect of inter-cell interference from other-cell base stations (BSs) but also eliminates intra-cell interference among spatial streams in the same cell. We show that the minimum number of users required to achieve a target degrees-of-freedom can be fundamentally reduced, i.e., the fundamental user scaling law can be improved by using the ODIA, compared with the existing downlink IA schemes. In addition, we adopt a limited feedback strategy in the ODIA framework, and then analyze the number of feedback bits required for the system with limited feedback to achieve the same user scaling law of the ODIA as the system with perfect channel state information. We also modify the original ODIA in order to further improve the sum-rate, which achieves the optimal multiuser diversity gain, i.e., $\log \log N$ , per spatial stream even in the presence of downlink inter-cell interference, where $N$ denotes the number of users in a cell. Simulation results show that the ODIA significantly outperforms existing interference management techniques in terms of sum rate in realistic cellular environments. Note that the ODIA operates in a non-collaborative and decoupled manner, i.e., it requires no information exchange among BSs and no iterative beamformer optimization between BSs and users, thus leading to an easier implementation.

Self-organizing inter-cell interference coordination in 4G and beyond networks using genetic algorithms

ABSTRACTThe design objective of the 4G and beyond networks is not only to provide high data rate services but also ensure a good subscriber experience in terms of quality of service. However, the main challenge to this objective is the growing size and heterogeneity of these networks. This paper proposes a genetic-algorithm-based approach for the self-optimization of interference mitigation parameters for downlink inter-cell interference coordination parameter in Long Term Evolution (LTE) networks. The proposed algorithm is generic in nature and operates in an environment with the variations in traffic, user positions and propagation conditions. A comprehensive analysis of the obtained simulation results is presented, which shows that the proposed approach can significantly improve the network coverage in terms of call accept rate as well as capacity in terms of throughput.

Uplink-Downlink LTE Multi Cell Capacity: A Performance Analysis in the Presence of ICI, Imperfect Channel Information and Reuse-1 Plan

Long Term Evolution (LTE) technology is based on Orthogonal Frequency Division Multiple Access (OFDMA) technique in the downlink to support multiple users in the same cell at the same time. Such system is known to be susceptible to Inter Cell Interference (ICI) in the downlink. The uplink technology of choice, however, has been SC-FDMA due to low power consumption requirement by the mobile terminal. In order to deliver higher data rates anywhere in the cell in the downlink, especially at the cell edge; many algorithms have been proposed for interference mitigation and avoidance which impose additional complexity on the system and yields minimum capacity enhancements. MIMO techniques have proven to be more efficient than such algorithms. In this paper, a performance analysis of LTE cell capacity is conducted in the presence of several MIMO deployments, where multiple antennas at both the transmitter and the receiver are considered. A comprehensive simulation study of different multiple antenna configurations in the presence of uplink and downlink ICI and cell edge throughput is presented. We also provide insights into the MIMO deployment of choice based on users SINR.

Graph-Based Multicell Scheduling in OFDMA-Based Small Cell Networks

This paper proposes a novel graph-based multicell scheduling framework to efficiently mitigate downlink intercell interference in OFDMA-based small cell networks. We define a graph-based optimization framework based on interference condition between any two users in the network assuming they are served on similar resources. Furthermore, we prove that the proposed framework obtains a tight lower bound for conventional weighted sum-rate maximization problem in practical scenarios. Thereafter, we decompose the optimization problem into dynamic graph-partitioning-based subproblems across different subchannels and provide an optimal solution using branch-and-cut approach. Subsequently, due to high complexity of the solution, we propose heuristic algorithms that display near optimal performance. At the final stage, we apply cluster-based resource allocation per subchannel to find candidate users with maximum total weighted sum-rate. A case study on networked small cells is also presented with simulation results showing a significant improvement over the state-of-the-art multicell scheduling benchmarks in terms of outage probability as well as average cell throughput.

Dynamic Clustering Framework for Multi-Cell Scheduling in Dense Small Cell Networks

This letter proposes a novel graph-based multi-cell scheduling framework to efficiently mitigate downlink inter-cell interference in small cell OFDMA networks. This framework incorporates dynamic clustering combined with channel-aware resource allocation to provide tunable quality of service measures at different levels. Our extensive evaluation study shows that a significant improvement in user's spectral efficiency is achievable, while also maintaining relatively high cell spectral efficiency via empirical tuning of re-use factor across the cells according to the required QoS constraints.

On the Expanded Region of Picocells in Heterogeneous Networks

In order to expand the downlink (DL) coverage areas of picocells in the presence of an umbrella macrocell, the concept of range expansion has been recently proposed, in which a positive range expansion bias (REB) is added to the DL received signal strengths (RSSs) of picocell pilot signals at user equipments (UEs). Although range expansion may increase DL footprints of picocells, it also results in severe DL inter-cell interference in picocell expanded regions (ERs), because ER picocell user equipments (PUEs) are not connected to the cells that provide the strongest DL RSSs. In this paper, we derive closed-form formulas to calculate appropriate REBs for two different range expansion strategies, investigate both DL and uplink (UL) inter-cell interference coordination (ICIC) to enhance picocell performance, and propose a new macrocell–picocell cooperative scheduling scheme to mitigate both DL and UL interference caused by macrocells to ER PUEs. Simulation results provide insights on REB selection approaches at picocells, and demonstrate the benefits of the proposed macrocell–picocell cooperative scheduling scheme over alternative approaches.

On the need for dynamic downlink intercell interference coordination for realistic Long Term Evolution deployments

Intercell interference is the main issue limiting the capacity of modern orthogonal frequency-division multiple access based cellular networks. Recently, extensive research work has been carried out in this field, and intercell interference coordination techniques have been recognized as key enablers of current and future cellular technologies. In this article, i a comprehensive survey of the most representative contributions is provided together with ii a generic methodology to measure their actual merit. The performance of several interference avoidance strategies has been evaluated both from system and user point of view in the context of a Long Term Evolution LTE-based network considering not only synthetic cellular scenarios but also realistic deployments. Our literature review indicates that there is a need for adaptive/operator-customizable low-complex intercell interference coordination ICIC schemes suitable for realistic LTE deployments. Results obtained by means of a comprehensive set of simulations corroborate and support this premise. In this article, it is shown that simultaneous gains in terms of spectral/energy efficiency and fairness can be achieved through dynamic mechanisms with respect to both classic hard reuse schemes and static ICIC techniques. Besides numerical results, a novel merit assessment methodology based on several weighted performance metrics is proposed. Our findings show that dynamic schemes outperform static techniques by around 20-35% in realistic deployments. Copyright © 2012 John Wiley & Sons, Ltd.

Performance Investigation on Cell Selection Schemes Associated with Downlink Inter-Cell Interference Coordination in Heterogeneous Networks for LTE-Advanced

In Long-Term Evolution (LTE)-Advanced, a heterogeneous network in which femtocells and picocells overlay macrocells is being extensively discussed in addition to traditional well-planned macrocell deployment to improve further the system throughput. In heterogeneous network deployment, cell selection as well as inter-cell interference coordination (ICIC) is very important to improve the system and cell-edge throughput. Therefore, this paper investigates three cell selection methods associated with ICIC in heterogeneous networks in the LTE-Advanced downlink: Signal-to-interference plus noise power ratio (SINR)-based cell selection, reference signal received power (RSRP)-based cell selection, and reference signal received quality (RSRQ)-based cell selection. The results of simulations (4 picocells and 25 sets of user equipment are uniformly located within 1 macrocell) that assume a full buffer model show that the downlink cell and cell-edge user throughput levels of RSRP-based cell selection are degraded by approximately 2% and 11% compared to those for SINR-based cell selection under the condition of maximizing the cell-edge user throughput due to the impairment of the interference level. Furthermore, it is shown that the downlink cell-edge user throughput of RSRQ-based cell selection is improved by approximately 5%, although overall cell throughput is degraded by approximately 6% compared to that for SINR-based cell selection under the condition of maximizing the cell-edge user throughput.

Uplink capacity analysis for multihop TDD-CDMA cellular system

Multihop TDD-CDMA cellular system becomes a promising candidate for fourth generation (4G) cellular systems because it provides wider coverage and higher throughput. In this paper, we analyze the uplink system capacity of a multihop TDD-CDMA cellular system. We first analyze a one-hop TDDCDMA cellular system with different base station's (BS's) direct coverage area. We find that the system capacity can be improved if a BS only covers a center small area of the cell. Besides, the high downlink transmission power of the surrounding BSs can degrade the capacity severely. Thus, we propose a multihop TDD-CDMA cellular system to overcome the high downlink inter-cell interference. In our system, a cell area is divided into two regions: inner-region and outer-region. The mobile users in the inner- and outer- region of the cell communicate with BS and relay station (RS), respectively. Based on this model, the uplink system capacity in both regions with the assumption that the inter-cell and intra-cell interference follow the Gaussian distribution is obtained. A comparison equation to provide a fair comparison with conventional one-hop TDD-CDMA cellular system is presented. From the results, we conclude that multihop TDD-CDMA cellular system can improve capacity significantly.

Cell Center/Edge Transmission Power Ratio Optimization to Mitigate Downlink Inter-Cell Interference in OFDM Systems

OFDM based systems should provide a high data rate for users at the cell edge. The spectrum efficiency must be improved significantly, and interference mitigation techniques should be reconsidered to satisfy the performance requirements and QoS for users throughout the cells. This paper extends the results of earlier studies on interference problems for the fractional frequency reuse (FFR) scheme using a system level simulator. The transmission power ratio of users in the cell center to those at cell edge is varied, and the user throughput is calculated to find the optimum transmission power ratio of 0.3.