Abstract

Pilot power allocation for Internet of Things (IoT) devices in massive multi‐input multioutput heterogeneous wireless sensor networks (MIMO‐HWSN) is studied in this paper. The interference caused by fractional pilot reusing in adjacent cells had a negative effect on the MIMO‐HWSN system performance. Reasonable power allocation for users can effectively weaken the interference. Motivated by the water‐filling algorithm, we proposed a suboptimal pilot transmission power method to improve the system capacity. Simulation results show that the proposed method can significantly improve the uplink capacity of the system and explain the influence of different pilot transmission power on the performance of the system, but the complexity of the system almost does not increase.

Highlights

  • Due to the continued development of 5G and the gradual proliferation of 6G, the wireless data traffic is estimated to reach the unprecedented quantity

  • Where ωb,c,k,q stands for the large-scale fading parameter of the i-th path, which contains the shadow fading and path-loss; Q denotes the path of the k-th macrocell SN (MSN) in the c-th cell to the b-th macrocell base stations (MBSs); vðθÞ indicates the steering vector; and θb,c,k,q denotes the AOA of the q-th path

  • The MBS demodulates the data according to the channel estimation ĥl,l,k, which is obtained in the previous stage

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Summary

Introduction

Due to the continued development of 5G and the gradual proliferation of 6G, the wireless data traffic is estimated to reach the unprecedented quantity. Reference [33] proposes a channel estimation method based on mutual cooperation between base stations (BSs) in the system This scheme uses additional second-order statistical information of channels to distinguish users. Reference [34] proposes a blind channel estimation method based on subspace projection without mutual cooperation between cells This blind channel estimation scheme is combined with an appropriate power allocation scheme which can effectively alleviate the pilot contamination in massive MIMO systems. A macrocell SN (MSN) uplink pilot transmit power allocation scheme based on location-aware channel estimation and a novel pilot allocation method is proposed and obtains the effects of different power allocations on improving massive MIMO-HWSN system performance. EfBg and TrðBÞ indicate the statistical expectation and the trace of B for random variables B

System Model
C Km qffiffiffiffiffiffiffiffiffiffi
A Novel Location-Aware Channel Estimation Method
Uplink Pilot Power Allocation Based on Water-Filling Algorithm
Simulation Result
Findings
Conclusion
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