A Novel Joint Spatial-Code Clustered Interference Alignment Scheme for Large-Scale Wireless Sensor Networks

Wu, Zhilu; Jiang, Lihui; Ren, Guoyu; Zhao, Nan; Zhao, Yaqin

doi:10.3390/s150101964

Cited by 10 publications

(6 citation statements)

References 39 publications

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“…A matrix‐based algorithm is proposed to reduce the complexity of the clustering process by sequential cell selection instead of the exhaustive search 21 . The users of a wireless sensor network are grouped to achieve feasible IA within each cluster 22 . A pseudo‐noise (PN) code is also assigned to each cluster to suppress the intercluster interference.…”

Section: Introductionmentioning

confidence: 99%

“…IA can remove interferences of a limited number of users since it has limited dimensions, for example, a limited number of antennas. In some papers, the orthogonal codes/resources are allocated to each cluster, 22,23 or all clusters share the same resources by assuming the strong interferences are inserted within the clusters and weak ones out of clusters 20,21 . In this paper, the cluster scheduling algorithm is proposed which selects the clusters to transmit at the same time slot (to share the same resources).…”

Section: Introductionmentioning

confidence: 99%

“…In the proposed clustering, IA and scheduling are accomplished to achieve better spectral efficiency. If the interferences power scales from a small value to a large one, the cluster scheduling changes from simultaneous transmission 20,21 to an orthogonal transmission 22,23 …”

Section: Introductionmentioning

confidence: 99%

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Interference alignment and scheduling in clustered partially connected small cell networks

Ghorbani

Falahati

2020

Int J Communication

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Interference alignment (IA) is a beneficial interference management technique in heterogeneous networks (HetNets). Bearing this in mind, we target partially connected networks of small cells that are allocated randomly in a macrocell, whereas IA feasibility conditions may not be satisfied. To address this issue, we propose a new scheme with novel clustering and scheduling algorithms that is accomplished in three stages. The proposed scheme is accomplished by knowing the connection matrix of the established links that is obtained by different threshold values in the first stage. In the second stage, a new clustering algorithm is proposed to separate the cells to groups in which IA is feasible, and the feedback overhead is reduced. In the last stage, cluster scheduling method is proposed to efficiently schedule the clusters. The cluster scheduling allows the selected clusters with trivial intercluster interferences to transmit at the same time slot. The simulation results indicate the improvement of achievable averaged sum rate by the proposed clustering and cluster scheduling.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Interference alignment and scheduling in clustered partially connected small cell networks

Ghorbani

Falahati

2020

Int J Communication

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“…For most IA approaches, the global and perfect channel state information (CSIT) must be available at each transmitter [13,14,15,16]. However, in practical situations such as in frequency division duplex (FDD) systems, the condition is difficult to implement.…”

Section: Introductionmentioning

confidence: 99%

A Novel Joint Power and Feedback Bit Allocation Interference Alignment Scheme for Wireless Sensor Networks

Wang

et al. 2017

Sensors

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It is necessary to improve the energy efficiency of batteries in wireless sensor networks (WSNs). The multiple-input multiple-output (MIMO) technique has become an important means to ameliorate WSNs, and interference management is the core of improving energy efficiency. A promising approach is interference alignment (IA), which effectively reduces the interference and improves the throughput of a system in the MIMO interference channels. However, the IA scheme requires perfect channel state information (CSI) at all transceivers in practice, which results in considerable feedback overhead. Thus, limited IA feedback has attracted much attention. In this paper, we analyze the throughput loss of the K-user MIMO interference channels when each transmitter delivers multiple streams in one slot, and derives the upper-bound of the system interference leakage and throughput loss. Then, to reduce the interference leakage and throughput loss for the MIMO interference alignment with limited feedback, a joint power and feedback bit allocation optimization scheme is proposed. The simulation results show that, compared with the conventional schemes, the presented optimal scheme achieves less residual interference and better performance in the system throughput.

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“…Thanks to its bright prospects IA has been extended to use in many scenarios such as OFDM systems [ 11 ], femtocell networks [ 12 ], and cognitive networks [ 13 , 14 ]. In particular, Wu et al [ 15 ] have leveraged the IA technique to mitigate the strong interference in large scale WSNs. In heterogeneous networks, Sharma et al [ 16 ] have proposed a novel spectral coexistence mechanism which takes advantage of the IA technique.…”

Section: Introductionmentioning

confidence: 99%

A Rapid Convergent Low Complexity Interference Alignment Algorithm for Wireless Sensor Networks

Jiang

Ren

et al. 2015

Sensors

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Interference alignment (IA) is a novel technique that can effectively eliminate the interference and approach the sum capacity of wireless sensor networks (WSNs) when the signal-to-noise ratio (SNR) is high, by casting the desired signal and interference into different signal subspaces. The traditional alternating minimization interference leakage (AMIL) algorithm for IA shows good performance in high SNR regimes, however, the complexity of the AMIL algorithm increases dramatically as the number of users and antennas increases, posing limits to its applications in the practical systems. In this paper, a novel IA algorithm, called directional quartic optimal (DQO) algorithm, is proposed to minimize the interference leakage with rapid convergence and low complexity. The properties of the AMIL algorithm are investigated, and it is discovered that the difference between the two consecutive iteration results of the AMIL algorithm will approximately point to the convergence solution when the precoding and decoding matrices obtained from the intermediate iterations are sufficiently close to their convergence values. Based on this important property, the proposed DQO algorithm employs the line search procedure so that it can converge to the destination directly. In addition, the optimal step size can be determined analytically by optimizing a quartic function. Numerical results show that the proposed DQO algorithm can suppress the interference leakage more rapidly than the traditional AMIL algorithm, and can achieve the same level of sum rate as that of AMIL algorithm with far less iterations and execution time.

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A Novel Joint Spatial-Code Clustered Interference Alignment Scheme for Large-Scale Wireless Sensor Networks

Cited by 10 publications

References 39 publications

Interference alignment and scheduling in clustered partially connected small cell networks

Interference alignment and scheduling in clustered partially connected small cell networks

A Novel Joint Power and Feedback Bit Allocation Interference Alignment Scheme for Wireless Sensor Networks

A Rapid Convergent Low Complexity Interference Alignment Algorithm for Wireless Sensor Networks

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