###### Abstract  
The high demand for multimedia applications in environmental monitoring, invasion detection, and disaster aid has led to the rise of wireless sensor network (WSN). With the increase of reliability and diversity of information streams, the higher requirements on throughput and quality of service (QoS) have been put forward in data transmission between two sensor nodes. However, lower spectral efficiency becomes a bottleneck in non-line-of-sight (NLOS) transmission of WSN. This paper proposes a novel nondata-aided error vector magnitude based adaptive modulation (NDA-EVM-AM) to solve the problem. NDA-EVM is considered as a new metric to evaluate the quality of NLOS link for adaptive modulation in WSN. By modeling the NLOS scenario as the \(\eta-\mu\) fading channel, a closed-form expression for the NDA-EVM of multilevel quadrature amplitude modulation (MQAM) signals over the \(\eta-\mu\) fading channel is derived, and the relationship between SER and NDA-EVM is also formulated. Based on these results, NDA-EVM state machine is designed for adaptation strategy. The algorithmic complexity of NDA-EVM-AM is analyzed and the outage capacity of NDA-EVM-AM in an NLOS scenario is also given. The performances of NDA-EVM-AM are compared by simulation, and the results show that NDA-EVM-AM is an effective technique to be used in the NLOS scenarios of WSN. This technique can accurately reflect the channel variations and efficiently adjust modulation order to better match the channel conditions, hence, obtaining better performance in average spectral efficiency. adaptive modulation; nondata-aided error vector magnitude; non-line-of-sight; \(\eta-\mu\) fading channel; wireless sensor network +
Footnote †: journal: Sensors  
can be adapted relative to the channel characteristics. Obviously, the key to adaptive modulation in NLOS link focuses on which metric is fit for, and how to make the adaptation strategy based on the metric. Signal-to-noise ratio (SNR) as a traditional performance metric has been used in evaluation channel quality [9; 10; 11]. Many existing works that approach the adaptive modulation problem are based on DA-SNR. In [12], the authors suggested preamble-aided channel quality estimation (i.e., DA-SNR) as a metric for channel adaptation to improve the link quality under dynamic interference of WSN. In [13], the authors explored the scheme by evaluation DA-SNR to select the modulation order for the transmitter; and [PERSON] and [PERSON] et al. [14; 15] optimized the switching levels of DA-SNR to improve the throughput performance. However, DA-SNR-AM research mostly focuses on DA-SNR estimation and switching level optimization for certain special channels, such as additive white Gaussian noise (AWGN) and Rayleigh fading channels, which cannot provide the general model for NLOS propagation scenario in a realistic WSN. On the other hand, the fixed time interval between these known data sequences results in a non-real-time evaluation of channel quality estimation, especially in the case of rapidly time-varying channels. Recently, the \(\eta-\mu\) distribution as a general fading distribution fits for the NLOS scenario [16], and it is proposed for modeling the fading channel in NLOS condition of WSN [17]. Meanwhile, the nondata-aided error vector magnitude (NDA-EVM) as a new performance metric is becoming increasingly popular in quantifying the performance of communication system [18]. This paper proposes NDA-EVM as a new performance metric for adaptive modulation (i.e., NDA-EVM-AM) in an NLOS scenario. The NDA-EVM reflects the dispersion range of the received symbols from the ideal constellation points [18]. As a symbol-level performance metric, it is sensitive to the degradation of a wireless system [19], and fluctuations in the NDA-EVM can reveal even small variations in channel fading. Unlike DA-SNR, the NDA-EVM can be used to infer some achievable system performance (e.g., the symbol error rate (SER), throughput and outage probability) even if packet reception fails [20].