In the following, we discuss our method of interferencedetection  which is a by-product of LNV-SC.2.1.4Method-2: Interference detection with local noisevariancesFrom Fig.5, it is observed that forKnumber of interferers,the vector of noise variancesσ2observes sharp anddistinguished rise in magnitude over the regions wherenoise is higher, i.e., where the narrowband interferers are
Kumaret al. EURASIP Journal on Wireless Communications and Networking(2019) 2019:224 Page 7 of 21Fig. 5LNV estimates corresponding to four ZigBee interferers. Distinguish lobes appear at ZigBee center frequencies due to LNV estimationpresent compared to the regions where the narrowbandinterferers are absent. For a given WiFi channel, the over-lapping ZigBee channels’ center frequencies are known apriori as shown in Fig.1. Thus the elevated portions inFig.5give a coarse estimate of the presence of the inter-ferers. We combine this knowledge along with a thresholddetector to pinpoint the interferers as soon as they appear.Once the interferers appear, the corresponding LNV isestimated, and the LLRs are scaled using LNV-SC. Theentire operation of interference detection and LLR scalingis illustrated in Fig.6.Our proposed method of interference detection doesnot add any additional signal processing complexity sinceit is a by-product of LNV-SC. The key advantage of ourapproach is that lobes could be obtained even at very lowlevels of interference. However, our method is effectiveonly when there is an overlap between LTS of WiFi andan ongoing ZigBee transmission as it uses LTS (duration0.8μs) to calculateσ2. In order to detect the appearance ofZigBee interference during an ongoing WiFi transmission,pilot subcarriers embedded under every OFDM data sym-bols of WiFi could be used; however, estimation accuracycould be affected.In the following, we discuss our work  which is amulti-antenna extension to LNV-SC.2.2Interference mitigation in multi-antenna WiFireceiversTheindoorchannel,especiallyinside,homeandindustries are rich in multipath . With the appropriatespatial separation between receiver antennas, the inter-ference power on different antennas will be different. We use this insight for applying multi-antennadiversity techniques along with our previous method ofsingle antenna, i.e., LNV-SC. We start our developmentby a primer on maximal-ratio combining, but first, weestablish the multi-antenna signal model.2.2.1Signal modelOur signal model consists of a dual-antenna WiFi receiver(WiFi-Rx), a single-antenna WiFi transmitter (WiFi-Tx),and a single-antenna ZigBee transmitter (ZB-Tx) as illus-trated in Fig.7.Fig. 6Flow chart of interference detection and LLR scaling. LLRscaling using LNV (LNV-SC) to be performed only during interference
Kumaret al. EURASIP Journal on Wireless Communications and Networking(2019) 2019:224 Page 8 of 21Fig. 7Signal model: single-antenna WiFi transmitter, single-antenna ZigBee interferer and two-antenna WiFi receiverAfter FFT, the received signal vectorYonith subcar-rier of
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