Dynamic Interference Coordination With Analytical Near-Optimal Power Allocation Toward High User Fairness

To mitigate interference on celledge users and improve fairness of the whole system, dynamic inter-cell interference coordination(ICIC) is one of the promising solutions. However, traditional dynamic ICIC is considered as an NP-hard problem and power variability further adds another dimension to this joint optimization issue, making it even more difficult to quickly reach a near-optimal solution. Therefore, we theoretically obtain the closed-form expression of the near-optimal power allocation ratio for users in adjacent cells paired in the same resource block and interfere each other, so that the total utility corresponding to α-fairness is maximized. Dynamic ICIC using this closed-form solution could improve user fairness without causing an increment of the computational complexity. Numerical results show that, compared with the schemes using identical power for different users, our method does not obviously degrade the system's average spectral efficiency.

Multicell power allocation method based on game theory for inter-cell interference coordination

As a new technology, coordinated multipoint （CoMP） transmission is included in LTE-Advanced study item. Moreover, the network architecture in LTE-Advanced system is modified to take into account coordinated transmission. Under this background, a novel power allocation game model is established to mitigate inter-cell interference with cellular coordination. In the light of cellular cooperation relationship and centralized control in eNodeB, the power allocation in each served antenna unit aims to make signal to interference plus noise ratio （SINR） balanced among inter-cells. Through the proposed power allocation game algorithm, the users＇ SINR can reach the Nash equilibrium, making it feasible to reduce the co-frequency interference by decreasing the transmitted power. Numerical results show that the proposed power allocation algorithm improves the throughput both in cell-center and cell-edge. Moreover, the blocking rate in cell-edge is reduced too.

Joint load balancing and interference coordination in multi-antenna heterogeneous networks

In heterogeneous networks（Het Nets）, it is desirable to offload users from macro cells to small cells to achieve load balancing. However, the offloaded users suffer a strong inter-tier interference. To guarantee the performance of the offloaded users, the interference from macro cells should be carefully managed. In this paper, we jointly optimize load balancing and interference coordination in multi-antenna Het Nets. Different from previous works, instead of almost blank subframes（ABS） on which the macro cells waste time resource, the macro cells suppress the interference to the offloaded users by zero-forcing beamforming（ZFBF） on interference nulling subframes（INS）. Considering user association cannot be conduct frequently, we derive the long-term throughput of users over Rayleigh fading channels while previous works focused on instantaneous rate. From the perspective of the spectrum efficiency and user fairness, we formulate a long-term network-wide utility maximization problem. By decomposing the problem into two subproblems, we propose an efficient joint load balancing and interference coordination strategy. Simulation results show that our proposal can achieve good system performance gains over counterparts in term of the network utility, cell edge throughput and average throughput.

Game-based distributed noncooperation interference coordination scheme in ultra-dense networks

Ultra-dense networks(UDNs) is a promising solution to meet the exponential increase in mobile data traffic. But the ultra-dense deployment of cells inevitably brings complicated inter-cell interference(ICI) and existing interference coordination scheme cannot be directly applied. To minimize the aggregate interference of each small cells, this paper formulated the problem as a distributed noncooperation game-based interference coordination scheme in UDNs considering the real demand rate of each small cell user equipment(SUE) and proved it to be a potential game. An improved no-regret learning algorithm was introduced to coverage to the Nash equilibrium(NE) of the formulated game. Simulation results show that the proposed scheme has better performance compared with existing schemes.

Power allocation scheme for multicell interference coordination in OFDMA systems

To coordinate inter-cell interference,a multicell adaptive power allocation scheme is proposed for downlink orthogonal frequency division multiple access(OFDMA)cellular systems.This scheme uses the difference of the signal to interference plus noise ratio(SINR)between the co-subchannels of adjacent cells to balance SINR for coordinating the transmit power in the co-subchannels.The scheme can improve edge user performance,reduce interference between the co-subchannels of adjacent cells and improve radio resource utility.Simulation results show that the scheme can balance system performance and ensure system throughput.

Load-adaptive frequency reuse scheme for inter-cell interference coordination in relay networks

Cellular relay networks adopting orthogonal frequency division multiple （OFDM） technology has been widely accepted for next generation wireless communication due to its advantage in enlarging coverage scale as well as improving data rate.In order to improve the performance of user equipments （UEs） near the cell edge,especially to avoid the interference from inter-cell and intra cell,an enhanced soft frequency reuse scheme is adopted in this paper to assure inter-cell interference coordination （ICIC）.Compared with traditional frequency allocation work,the proposed scheme is interference-aware and load-adaptive,which dynamically assigns available frequency among UEs under certain schedule method in variable traffic load condition and mitigates interference using information provided by interference indicator.It can improve signal-to-interference plus noise ratio （SINR） of the UE in each sub channel thus enable the system achieve better throughput and blocking probability performance.Simulation results prove that the proposed scheme may achieve desirable performance on throughput,blocking probability and spectral utilization in the sector under different traffic load compared with other schemes.

A New Strategy for Dynamic Channel Allocation in CR-WMN Based on RCA

Channel assignment has emerged as an essential study subject in Cognitive Radio-basedWireless Mesh Networks(CR-WMN).In an era of alarming increase in Multi-Radio Multi-Channel(MRMC)network expansion interference is decreased and network throughput is significantly increased when non-overlapping or partially overlapping channels are correctly integrated.Because of its ad hoc behavior,dynamic channel assignment outperforms static channel assignment.Interference reduces network throughput in the CR-WMN.As a result,there is an extensive research gap for an algorithm that dynamically distributes channels while accounting for all types of interference.This work presents a method for dynamic channel allocations using unsupervisedMachine Learning(ML)that considers both coordinated and uncoordinated interference.Unsupervised machine learning uses coordinated and non-coordinated interference for dynamic channel allocation.To determine the applicability of the proposed strategy in reducing channel interference while increasingWMNthroughput,a comparison analysis was performed.When the simulation results of our proposed algorithm are compared to those of the Routing Channel Assignment(RCA)algorithm,the throughput of our proposed algorithm has increased by 34%compared to both coordinated and non-coordinated interferences.

Challenges for beyond 5G:ultra-densification of radio access network

Ultra-densification of radio access network(RAN)is a key to efficiently support the exponentially growing mobile data traffic in 5 G era.Furthermore,extremely high frequency band like mm Wave band was utilized to solve the bandwidth shortage problem.However,untra-dense reusing the same radio resource produced severe interference.And the mm Wave link was very harsh due to frequent blockage by obstacles.Therefore a new RAN architecture needed to be introduced to realize ultra-reliable communications in such a severe radio propagation environment.An architecture of distributed MIMO based RAN was presented.Then,enhanced interference coordination(e IC)was described.Finally,the effectiveness of distributed MIMO based RAN with e IC by computer simulation was showed.

Clustering-based adaptive low-power subframe configuration with load-aware offsetting in dense heterogeneous networks

Heterogeneous Networks(HetNets)and cell densification represent promising solutions for the surging data traffic demand in wireless networks.In dense HetNets,user traffic is steered toward the Low-Power Node(LPN)when possible to enhance the user throughput and system capacity by increasing the area spectral efficiency.However,because of the transmit power differences in different tiers of HetNets and irregular service demand,a load imbalance typically exists among different serving nodes.To offload more traffic to LPNs and coordinate the Inter-Cell Interference(ICI),Third-Generation Partnership Project(3GPP)has facilitated the development of the Cell Range Expansion(CRE),enhanced Inter-Cell Interference Coordination(eICIC)and Further enhanced ICIC(FeICIC).In this paper,we develop a cell clustering-based load-aware offsetting and an adaptive Low-Power Subframe(LPS)approach.Our solution allows the separation of User Association(UA)functions at the User Equipment(UE)and network server such that users can make a simple cell-selection decision similar to that in the maximum Received Signal Strength(max-RSS)based UA scheme,where the network server computes the load-aware offsetting and required LPS periods based on the load conditions of the system.The proposed solution is evaluated using system-level simulations wherein the results correspond to performance changes in different service regions.Results show that our method effectively solves the offloading and interference coordination problems in dense HetNets.

Dynamic bias setting for range extension in LTE-advanced macro-pico heterogeneous networks

In co-channel deployment of macro cell and pico cells, cell range extension （RE）, a simple and typical cell association scheme, is introduced to achieve better load balancing and improve cell edge performance. In this article, a novel dynamic and distributed bias setting scheme is proposed for RE technique in macro-pico heterogeneous networks. In this strategy, the worst user throughput of each cell during an adjusting time interval T is obtained to change the bias values according to certain procedures, where an introduced indicator is used to freeze the possibility of increasing bias value if needed. Furthermore, silent state and coarse control process are employed to achieve low overheads and computational complexity. Simulation results show that the proposed scheme can greatly improve the cell-edge performance compared with the static bias setting strategies, while maintaining the overall cell performance at the same time.

An adaptive random access strategy for multi-channel relaying networks

In this paper, an adaptive random access strategy is presented for multi-channel relaying networks to address the issue of random access of the non-real-time （NRT） services. In the proposed scheme, NRT services access the base station （BS） by first accessing the nearest relay node （RN）. When collision occurs, for the sake of fast and efficient access, the user will begin a frequency domain backoff rather than randomly retry in time domain. A remarkable feature of this scheme is that the RN will adaptively determine the maximum allowed frequency backoff window at each access period. This is achieved according to the new arrival rate as well as the number of available access channels. Moreover, to alleviate the interference caused by sub-channel reuse among RNs, a fractional frequency reuse scheme is also considered. The analysis and numerical results demonstrate that our scheme achieves higher throughput, lower collision probability and lower access delay than conventional slotted Aloha as well as the scheme without frequency backoff window adaptation.

Optimal and constant power allocation for joint transmission in HetNet

This paper investigates the power allocation issues for joint transmission in heterogeneous network （HetNet）, which is characterized by severe cross-tier interference. The optimization problem of maximizing the HetNet throughput is formulated. The original problem turns out to be a non-convex problem, the global optima of which cannot be obtained by conventional optimization methods. This paper develops a novel method to achieve the global optima by tuming the original problem into quasi-convex problem. In addition, this paper considers a constant power allocation scheme, as a tradeoff between the system throughput and computational complexity. Based on duality gap theory, the bound of constant power allocation scheme is mathematically derived. Numerical results under different system parameters indicate that both the proposed schemes outperform conventional interference coordination schemes.