Interference Alignment in Two-Tier Randomly Distributed Heterogeneous Wireless Networks Using Stochastic Geometry Approach

Abstract

Abstract-With the massive increase in wireless data traffic in recent years, multi-tier wireless networks have been deployed to provide much higher capacities and coverage. However, heterogeneity of wireless networks bring new challenges for interference analysis and coordination due to spatial randomly distributed transmitters. In this paper, we present a distancedependent interference alignment (IA) approach for a generic 2-tier heterogeneous wireless network, where transmitters in the first a nd s econd t iers a re d istributed a s P oisson Point Process (PPP) and Poisson Cluster Process (PCP) respectively. The feasibility condition of the IA approach is used to find upper bound of the number of interference streams that can be aligned. The proposed IA scheme maximizes the second-tier throughput by using the trade-off between signal-to-interference ratio and multiplexing gain. It is shown that acquiring accurate knowledge of the distance between the receiver in the second-tier and the nearest cross-tier transmitter only brings insignificant throughput gain compared to statistical knowledge of distance. Furthermore, the remaining cross-tier and inter-cluster interferences are modeled and analyzed using stochastic geometry technique. Numerical results validate the derived expressions of success probabilities and throughput, and show that the distancedependent IA scheme significantly outperforms the traditional IA scheme in the presence of path-loss effect.

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

“…Asymptotic IA is an opportunistic technique that exploits the presence of complementary channel states in equal magnitudes to achieve linear IA [28]. [33][34][35][36] Distributed IA Local Single [37][38][39][40] Subspace IA Perfect Multi [29,[41][42][43] Blind IA Absent Single [25,44,45] Ergodic IA Perfect/delayed Single [36,46,47] Retrospective IA Delayed Single [26,39,43] Lattice Alignment Perfect Single [40,[48][49][50][51] IA and Cancelation Perfect Single/Multi [27,52,53] Opportunistic IA Perfect Single/Multi [28,54,55] Asymptotic IA Perfect Single…”

“…Applications [56][57][58][59][60] Cognitive Radio Networks [30,41,47,61] K User Interference Channel [27,30,31,46,47] K User M × N MIMO Interference Channels [62,63] 5G Cellular Wireless Networks [64][65][66] Cooperative Interference Networks [66,67] Multihop Interference Networks [68,69] Ad hoc Networks [70,71] Physical Layer Security [72,73] Satellite Networks [74,75] D2D Networks [50,76] IoT Networks [34,35,38,51] Heterogeneous Networks…”

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

“…In [18], according to the distances between different Tx-Rx pairs, the whole network was divided into only one IA subnetwork (i.e., a cluster) and several spatial multiplexing subnetworks with each consisting of only one user and far away from the IA subnetwork. In [19], through poisson cluster process in a generic two-tier heterogeneous wireless network, all Tx-Rx pairs were grouped into disjoint clusters with the same size according to the distance between transmitters and receivers, and IA was performed within each cluster to maximize the second-tier throughput by using the tradeoff between signalto-interference ratio and multiplexing gain. In dense SCNs, however, some of the inter-cluster interference is still strong and cannot be treated as noise.…”

“…Proof: See Appendix A. Subproblem (19) is equivalent to the NP-hard subproblem (17), so it is also NP-hard. However, as an efficient solution, we can recursively partition graph G through the minimum cut criterion, and the well-known Stoer-Wagner (S-W) algorithm proposed in [34] can be used to compute the minimum cut of an arbitrary subgraph of G. Firstly, graph G will be partitioned into two subgraphs G 1 and G 2 by S-W algorithm.…”

Interference cancellation in HetNet uplink with and without MU‐CSIR: a subspace‐based approach

“…In order to alleviate the effect of interference to enhance the system performance, different IM techniques have been proposed in [4–15] and the reference therein. A coordinated multiple point (CoMP) technique developed in [4] improves the quality of service (QoS) for cell‐edge users.…”