A Cross Time Slot Partial Interference Alignment Scheme in Two-Cell Relay Heterogeneous Networks

Qin, Cai; Wang, Chaowei; Pan, Du; Wang, Weidong; Zhang, Yinghai

doi:10.3390/app9040652

Cited by 5 publications

(8 citation statements)

References 18 publications

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“…Here it is worth mentioning that in dense SCNs, using exhaustive search to find the optimal solution to problem (8) will lead to unaffordable computational complexity. So we utilize Algorithms 1 and 2 to group all SBS-SUE pairs into disjoint clusters, and then utilize exhaustive search to obtain the optimal solution to the subproblem of subchannel allocation for the formed clusters (OSAC), i.e., subproblem (21), which can be regarded as an efficient approximation of the optimal solution to problem (8). It is also noteworthy that the performance curve of OSAC and those of five other solutions are obtained by taking the average of 5 and 200 realizations, respectively.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…In [20], an efficient approach was proposed to judge the feasibility condition of IA in full-duplex-enabled SCNs by relaxing the corresponding optimization problem into a linear programming one, and then an adaptive power allocation scheme based IA was proposed for interference elimination. In [21], by aligning the interference generated in different time slots to the same subspace, a scheme of time slot allocation based on partial IA was proposed to simultaneously mitigate both the inter-cell and intra-cell interference in a two-cell relay heterogeneous networks. However, in dense SCNs, without clustering, it is infeasible to mitigate all the interference to further meet the massive number of data stream requirements for all SUEs only by exploiting resource allocation based on IA.…”

Section: A Ia With Clustering and Resource Allocation Based On Iamentioning

confidence: 99%

“…Subproblem (21) is also NP-hard owing to the combinatorial nature of subchannel allocation. Because each cluster performing IA still contains multiple vertices without intra-cluster interference among them, so subproblem (21) is quite different from the traditional subchannel allocation problems. Fortunately, each cluster can be further treated as a vertex, which is also adopted in [23].…”

Section: B Phase 2: Subchannel Allocation By the Proposed Graph Colomentioning

confidence: 99%

“…Next we utilize the proposed graph coloring algorithm which has a lower complexity to obtain a suboptimal but efficient solution to (21). Briefly speaking, each subchannel is represented by one color, and if two vertices in V G s is connected with one edge, they must be allocated with different colors; otherwise, they can be allocated with the same colors.…”

Section: B Phase 2: Subchannel Allocation By the Proposed Graph Colomentioning

confidence: 99%

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Resource Allocation Based on Interference Alignment With Clustering for Data Stream Maximization in Dense Small Cell Networks

2019

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In this paper, by allocating the limited subchannel resources based on interference alignment (IA) with clustering to mitigate the severe co-tier interference in dense small cell networks (SCNs), we aim at maximizing the number of data streams achieved by all small cell user equipments (SUEs) while guaranteeing the data stream requirement for each SUE. As the corresponding optimization problem is NP-hard, we propose a two-phases algorithm based on graph theory to obtain a suboptimal but efficient solution, which requires much lower complexity and notably reduced feedback overhead. In the first phase, all SBS-SUE pairs are grouped into disjoint clusters by the recursive partition of the constructed graph, where the edge weight is only determined by the path losses from small cell base stations (SBSs) to SUEs, so the estimation of perfect global channel state information (CSI) is avoided. Furthermore, when guaranteeing that IA is feasible within each cluster, the number of formed clusters and the size of each cluster are determined by the distributions of dense SCNs instead of being specified. In the second phase, by further treating each cluster as a new vertex, graph coloring algorithm is proposed for subchannel allocation, which only requires to estimate the perfect CSI within each cluster. The analysis of computational complexity demonstrates that the proposed two-phases algorithm has a much lower complexity compared with the optimal solution obtained by the exhaustive search. Numerical results show that the proposed solution outperforms other related schemes and exhibits a performance close to the optimal solution. INDEX TERMS Clustering, data streams, dense small cell networks (SCNs), graph coloring, graph partitioning, interference alignment (IA), subchannel allocation.

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Section: Numerical Resultsmentioning

confidence: 99%

Section: A Ia With Clustering and Resource Allocation Based On Iamentioning

confidence: 99%

Section: B Phase 2: Subchannel Allocation By the Proposed Graph Colomentioning

confidence: 99%

Section: B Phase 2: Subchannel Allocation By the Proposed Graph Colomentioning

confidence: 99%

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Resource Allocation Based on Interference Alignment With Clustering for Data Stream Maximization in Dense Small Cell Networks

2019

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“…The algorithm optimized the attributes such as fairness among users, spectral efficiency and battery lifetime. Relay-based HetNets were considered by the authors of [19], wherein, they proposed a method to suppress inter-cell and intra-cell interference. Their proposed scheme was shown to outperform existing baseline methods in terms of sum-rate performance.…”

Section: A Related Workmentioning

confidence: 99%

Power Allocation and User Assignment Scheme for beyond 5G Heterogeneous Networks

Bakht

Jameel

Ali

et al. 2019

Wireless Communications and Mobile Computing

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The issue of spectrum scarcity in wireless networks is becoming prominent and critical with each passing year. Although several promising solutions have been proposed to provide a solution to spectrum scarcity, most of them have many associated tradeoffs. In this context, one of the emerging ideas relates to the utilization of cognitive radios (CR) for future heterogeneous networks (HetNets). This paper provides a marriage of two promising candidates (i.e., CR and HetNets) for beyond fifth generation (5G) wireless networks. More specifically, a joint power allocation and user assignment solution for the multi-user underlay CR-based HetNets has been proposed and evaluated. To counter the limiting factors in these networks, the individual power of transmitting nodes and interference temperature protection constraints of the primary networks have been considered. An efficient solution is designed from the dual decomposition approach, where the optimal user assignment is obtained for the optimized power allocation at each node. The simulation results validate the superiority of the proposed optimization scheme against conventional baseline techniques.

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The interference alignment scheme based on subspace differentiation for multicell multiuser multiple‐input‐multiple‐output uplink channels

Guo

et al. 2020

Trans Emerging Tel Tech

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The traditional subspace interference alignment (IA) schemes in the multicell multiuser multiple-input-multiple-output (MIMO) network align interference into the multidimensional subspace to reduce the dimension of the interference space, but the choice of subspace is random, and the difference between users is not considered. Such schemes may leave large intercell interference when the difference between users is large. To solve this problem, this article proposes the IA scheme based on subspace differentiation for multicell multiuser MIMO uplink channels. First, based on the transmit power and the distance to base stations in other cells, each user analyzes the interference value it will cause. The interference value of each user is represented by actual interference power (AIP). Within each cell, the users are reordered according to the AIP. When performing interference reduction, the signals of the users with large interference are merged into the subspace composed of the signals of the users with small interference, which can further reduce the final intercell interference. The multidimensional merge weight is assigned according to the AIP. The smaller the interference value of the dimension, the more interference it merges. The experimental simulation data show that the scheme implemented in this article can improve the proportion of the desired signals in the received signals of the receivers, thereby improving the overall system rate. When the user difference in transmit power and distance is large, the proposed scheme has a particularly obvious advantage.

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A Cross Time Slot Partial Interference Alignment Scheme in Two-Cell Relay Heterogeneous Networks

Cited by 5 publications

References 18 publications

Resource Allocation Based on Interference Alignment With Clustering for Data Stream Maximization in Dense Small Cell Networks

Resource Allocation Based on Interference Alignment With Clustering for Data Stream Maximization in Dense Small Cell Networks

Power Allocation and User Assignment Scheme for beyond 5G Heterogeneous Networks

The interference alignment scheme based on subspace differentiation for multicell multiuser multiple‐input‐multiple‐output uplink channels

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