Decentralized intercell interference coordination for fair resource allocation in large-scale networks

Inter-cell interference is a serious problem in multicell OFDMA systems. In this paper, an iterative interference price based power allocation algorithm with inter-cell interference coordination is proposed for downlink multi-cell OFDMA systems. In the algorithm, each base station announces a price for interference and performs power allocation based on the price information received from other base stations with the objective of maximizing the net utility of the local cell. Through price information updating and transmit power reallocation in every iteration, the algorithm can intelligently coordinate the inter-cell interference in the system. Besides, the algorithm can be implemented distributedly with price information shared among neighboring cells. Considering the heavy feedback overhead from the users to the base stations, a simplified algorithm which considers only the major interference is also proposed. Simulation results show that when the inter-cell interference is serious, the proposed algorithms can effectively increase the transmission rate compared with iterative water-filling.

In order to achieve high data rates in future wireless packet switched cellular networks, aggressive frequency reuse is inevitable due to the scarcity of the radio resources. While intra-cell interference is mostly mitigated and can be ignored, inter-cell interference can severely degrade performances with bad channel quality. Hence, Inter-Cell Interference Coordination (ICIC) is commonly identified as a key radio resource management mechanism to enhance system performance of 4G networks. This paper addresses the problem of ICIC in the downlink of Long Term Evolution (LTE) systems where the resource selection process is apprehended as a potential game. Proving the existence of Nash Equilibriums (NE) shows that stable resource allocations can be reached by selfish Base Stations (BS). We put forward a fully decentralized algorithm based on replicator dynamics to attain the pure NEs of the modeled game. Each BS will endeavor to select a set of favorable resources with low interference based on local knowledge only making use of signaling messages already present in the downlink of LTE systems.

Recent demand for capacity increase in mobile communications urges the development of both multiple- input multiple-output (MIMO) and small cells. However, overlapping coverage areas between neighboring small cells results in interference-limited networks, where the capacity of the network is severely degraded without superior intercell interference management (IIM) techniques. As one of the superior IIM techniques, the power control intercell interference coordination (ICIC) optimizes downlink transmit powers in the network. This paper proposes an IIM scheme consisting of both neural networks (NNs) power control on the transmitter side and interference cancellation (IC) on the receiver side. Computer simulations examine networks of MIMO systems with the power optimization using some ICIC algorithms: NN, the greedy search, the belief propagation (BP), and the maximum power, combined with IC on the receiver side. In addition, the deep learning, a breakthrough technique for NN with multi-layer structures, is also applied to mobile communications. The results show that the performance of NN is very close to that of the greedy search and superior to that of BP. Complexity of NN is much less than that of BP, and thus NN is suitable for IIM. It is also demonstrated that employing IC provides high capacity gain.

Inter-cell interference is a major issue in current wireless cellular systems, in particular with the development of femto-cells. Efficient macro-femto inter-cell interference coordination (ICIC) is crucial and should be performed with minimum communication between macro and femto base stations. We propose an ICIC approach, in which each femto base station informs a server about its position, obtains relevant information from mobile terminal measurements stored in a database maintained by the server and configures its transmission power according to this information. This power setting aims at maintaining a controlled impact of the femto base station on macro-cell performance, independent of the femto-cell location. In a 3GPP-LTE context, this approach exhibits a good femtomacro performance trade-off and is robust against power and positioning measurement errors.

Multiuser Orthogonal Frequency Division Multiple Access (OFDMA) networks, such as Long Term Evolution networks, use the frequency reuse-1 model to face the tremendous increase of mobile traffic demands, and to increase network capacity. However, inter-cell interference problems are generated, and they have a negative impact on cell-edge users performance. Resource and power allocation should be managed in a manner that alleviates the negative impact of inter-cell interference on system performance. In this paper, we formulate a novel centralized multi-cell resource and power allocation problem for multiuser OFDMA networks. The objective is to maximize system throughput while guaranteeing a proportional fair rate for all the users. We decompose the joint problem into two independent problems: a resource allocation problem and a power allocation problem. We prove that each of these problems is a convex optimization problem, and that their optimal solution is also an optimal solution to the original joint problem. Lagrange duality theory and subgradient projection method are used to solve the centralized power allocation problem. We study the convergence of our centralized approach, and we find out that it reduces inter-cell interference, and increases system throughput and spectral efficiency in comparison with the frequency reuse-1 model, reuse-3 model, fractional frequency reuse, and soft frequency reuse techniques.

In next generation wireless systems such as Long Term Evolution (LTE), Radio Resource Management with Inter-cell Interference Coordination (ICIC), is a key issue to be addressed. Although centralized resource allocation (RA) and collaborative processing can optimally perform ICIC, the overall required complexity suggests the consideration of distributed techniques. In this paper we investigate the behavior of distributed RA strategies aimed at maximizing the weighted average sum-rate of a multi-cell clustered system in presence of power constraints by evaluating throughput gap and fairness with respect to their respective centralized implementations. In the distributed RA strategies the inter-cell interference is partially coordinated through the use of power planning schemes (fractional frequency reuse - FFR - is the case considered here), leading to a reduction in both signaling and feedback requirements. The results obtained show that the distributed RA with aggressive frequency reuse is able to approach t performance of the centralized RA when the number of users is large. However, FFR is useful to improve fairness (or cell-edge user performance) at the expense of sum-rate when the scheduling weights are those of proportional fair scheduling (PFS), whereas FFR and in general power planning techniques are able to improve throughput while preserving the fairness when the scheduling weights are set to guarantee equal average rate to users.

This paper studies the suppression of cross-tier intercell interference (ICI) generated by a macro base station (MBS) to pico user equipments (PUEs) in heterogeneous networks (HetNets). Different from existing ICI avoidance schemes such as enhanced ICI cancellation (eICIC) and coordinated beamforming, which generally operate at the MBS, we propose a full duplex (FD)-assisted ICI cancellation (fICIC) scheme, which can operate at each pico BS (PBS) individually and is transparent to the MBS. The basic idea of the fICIC is to apply FD technique at the PBS such that the PBS can send the desired signals and forward the listened cross-tier ICI simultaneously to PUEs. We first consider the narrowband single-user case, where the MBS serves a single macro UE and each PBS serves a single PUE. We obtain the closed-form solution of the optimal fICIC scheme, and analyze its asymptotical performance in ICI-dominated scenario. We then investigate the general narrowband multiuser case, where both MBS and PBSs serve multiple UEs. We devise a low-complexity algorithm to optimize the fICIC aimed at maximizing the downlink sum rate of the PUEs subject to user fairness constraint. Finally, the generalization of the fICIC to wideband systems is investigated. Simulations validate the analytical results and demonstrate the advantages of the fICIC on mitigating cross-tier ICI.

This paper focuses on the design of vector perturbation (VP) precoding for coordinated multi-point (CoMP) multi-user downlink transmission. Precoding is performed by individual base stations (BSs) in a distributed manner using only the downlink channel coefficients and user data local to a BS. A cascade precoder structure with an outer precoder managing the inter-cell interference (ICI) and an inner precoder performing mean-squared-error (MSE) minimization-based VP to mitigate the intra-cell interference is proposed. Three different outer precoding techniques are considered. In the first technique, the outer precoder is designed to fully eliminate the ICI by trading off the degrees of freedom (DoFs) available through multiple antennas. While the proposed technique outperforms existing conventional-VP based designs, a large portion of DoF is consumed by the ICI elimination. To overcome this issue, in the second technique, interference alignment-based outer precoding that minimizes the total leakage interference is proposed. To further improve the system performance, in the third approach, precoding by joint minimization of total leakage interference plus MSE is performed. Numerical results show that the proposed cascade precoding structure is an efficient way to use the DoF of CoMP multi-user downlink transmission.

In this paper, we propose a novel frequency block-dependent online probabilistic activation control of base stations (BSs) in heterogeneous networks where low transmission-power pico-BSs are overlaid onto the coverage of a high-transmission-power macro-BS. The aim of the proposed method in this paper is to increase the system throughput within the system coverage using adaptive activation/deactivation of BSs depending on the location of the BSs and user terminals. By defining multiple frequency blocks in the overall system bandwidth and performing activation control on a per frequency block basis, we achieve an inter-cell interference coordination (ICIC) effect in addition to the overall reduction in inter-cell interference. The proposed method does not rely on complicated inter-BS cooperation. It uses inter-BS cooperation only to share the temporal system throughput observed for the entire system coverage. Based on the shared temporal system throughput information, each BS independently performs online activation control for the respective frequency blocks in a probabilistic manner. We also investigate an iterative algorithm to improve the convergence performance of the proposed method. Computer simulation results, in which the mobility of the user terminals is taken into account, show the effectiveness of the proposed method.

Non-orthogonal multiple access (NOMA) is promoted as a key component of 5G cellular networks. As the name implies, NOMA operation introduces intracell interference (i.e., interference arising within the cell) to the cellular operation. The intracell interference is managed by careful NOMA design (e.g., user clustering and resource allocation) along with successive interference cancellation. However, most of the proposed NOMA designs are agnostic to intercell interference (i.e., interference from outside the cell), which is a major performance limiting parameter in 5G networks. This paper sheds light on the drastic negative-impact of intercell interference on the NOMA performance and advocates interference-aware NOMA design that jointly accounts for both intracell and intercell interference. To this end, a case study for fair NOMA operation is presented and intercell interference mitigation techniques for NOMA networks are discussed. This paper also investigates the potential of integrating NOMA with two important 5G transmission schemes, namely, full duplex and device-to-device communication. This is important since the ambitious performance defined by the third generation partnership project for 5G is foreseen to be realized via seamless integration of several new technologies and transmission techniques.

The peculiar line-of-sight (LoS) propagation in air-to-ground channel provides both opportunities and challenges for the emerging cellular-connected unmanned aerial vehicle (UAV) communications. On one hand, the LoS channels make more cellular base stations (BSs) visible to a UAV as compared to ground users, which leads to a higher macro-diversity gain as compared to the ground users. On the other hand, the LoS channels also render the UAV to generate/receive more severe uplink/downlink interference to/from the BSs, thus requiring more sophisticated inter-cell interference coordination (ICIC) techniques with more BSs involved. To draw essential insight, this paper studies the uplink transmission from a UAV to cellular BSs. To mitigate the UAV's interference effect, we aim to maximize the sum-rate of the UAV and all ground users in its resulted ICIC region by jointly optimizing the UAV's cell association, resource block (RB) allocation, and transmit power. We first propose a centralized ICIC design that achieves the optimal performance. As the centralized ICIC requires global information of the network and substantial information exchange among an excessively large number of BSs, we further propose a decentralized ICIC scheme of significantly lower complexity and overhead for implementation. Specifically, we divide the cellular BSs into clusters, each with a dedicated cluster head for collecting information from its cluster BSs and exchanging information with the UAV by exploiting the LoS-induced macro-diversity. Numerical results show that the proposed decentralized ICIC scheme achieves a performance close to the optimal centralized design, and also outperforms the traditional ICIC scheme for cellular networks with terrestrial interference only.

In a Poisson Point Process (PPP) network model, in which the locations of Base Stations (BSs) are randomly distributed according to a Spatial Poisson Process, has been recently used as a tractable stochastic model to analyse the performance of downlink Heterogeneous Cellular Networks (HCNs). The HCN is modelled as a multi-tier cellular network where each tier is characterised by the transmission power level, propagation path loss exponent and density of BSs. The current works on HCN enabling Intercell Interference Coordination (ICIC) technique usually deal with Strict Frequency Reuse (FR) or Soft FR with a reuse factor of $\Delta=1$ in a Rayleigh fading channel. It has been assumed that all Base Stations (BSs) transmit continuously which leads to a reduction on the impact of number of users and RBs on network performance. In this paper, the performance of Soft FR with a reuse factor of $\Delta>1$ in Rayleigh-Lognormal fading channel is evaluated. The impact of the number of users and Resource Blocks (RBs) on Intercell Interference (ICI) are presented for Round Robin scheduling and indicator functions. The results show that there are opposite trends between coverage probability of Cell-Center User (CCU) and Cell-Edge User (CEU).

This paper studies the mitigation of cross-tier inter-cell interference (ICI) generated by a macro base station to a small-cell user equipment (SUE) in heterogeneous networks. A full-duplex (FD) based successive ICI cancellation (SIC) scheme, called fSICIC, is devised by applying FD technique at the small-cell base station (SBS). The basic idea of the fSICIC is to let the SBS send the desired signal and forward the overheard cross-tier ICI simultaneously to the SUE, where the forwarded ICI is controlled to enhance the ICI at the SUE to facilitate SIC. We first investigate the feasibility of the fSICIC, and then optimize the fSICIC to maximize the data rate of the SUE. Simulation results demonstrate the advantages of the fSICIC on mitigating cross-tier ICI, especially for strong ICI.

This paper presents a novel downlink resource allocation scheme for OFDMA-based next generation wireless networks subject to inter-cell interference (ICI). The scheme consists of radio resource and power allocations, which are implemented separately. Low-complexity heuristic algorithms are first proposed to achieve the radio resource allocation, where graph-based framework and fine physical resource block (PRB) assignment are performed to mitigate major ICI and hence improve the network performance. Given the solution of radio resource allocation, a novel distributed power allocation is then performed to optimize the performance of cell-edge users under the condition that desirable performance for cell-center users must be maintained. The power optimization is formulated as an iterative barrier-constrained water-filling problem and solved by using the Lagrange method. Simulation results indicate that our proposed scheme can achieve significantly balanced performance improvement between cell-edge and cell-center users in multi-cell networks compared with other schemes, and therefore realize the goal of future wireless networks in terms of providing high performance to anyone from anywhere.

How good is the performance of the existing Inter-Cell Interference Coordination (ICIC) schemes when dealing with users moving at high speeds? In this paper, we evaluate a number of existing schemes under high user mobility conditions. Then, we propose a dynamic decentralized ICIC scheme that requires no apriori frequency planning. The proposed scheme minimizes the amount of data needs to be exchanged among base stations. The scheme uses the Harmony Search (HS) algorithm in order to rapidly generate a more accurate User-to-Channel allocation matrix to cope with high user mobility. In addition, we propose strategies for power control and channel restriction in order to minimize the power consumption and inter-cell interference. A key advantage in the proposed scheme is that its computations are independent of the number of users and cells in the network. Extensive simulations demonstrate that, with a slight degradation in fairness, the proposed scheme provides 18% throughput improvements to edge users without penalizing other users. In addition, the use of the power control and restriction strategies has led to a 22% reduction in power consumption.