Local Convexity Inspired Low-Complexity Noncoherent Signal Detector for Nanoscale Molecular Communications

Non-Linear Signal Detection for Molecular Communications

“…At the receptor, a detector will sample the concentration of signaling molecules with the Nyquist rate R = 1/T b [8], [10]. After doing so, the discrete signal becomes:…”

“…In the above coherent MAP, the accurate estimation of CIR will be indispensable in evaluating likelihood densities. As seen, the complexity of such an MAP scheme comes from the sequential evaluation of likelihood densities [10].…”

“…Two counterparts are considered here, i.e. the coherent MAP detection and the noncoherent detection (which is similarly based on local convexity) [10]. For the MAP scheme, we assume the diffusive CSI h(t) has been accurately estimated, which may additionally consume the considerable time (e.g.…”

“…The linear noncoherent detector in ref. [10] relies similarly on the convexity shape of molecular concentration, which will effectively alleviate the computation burden and hence is applicable to low-complexity scenarios. However, such two linear detectors acquire satisfactory performances only in high SNRs (e.g.…”

“…First, acquiring unknown CSI in diffusion channels is resource demanding and difficult practically. Second, in order to mitigate the inter-symbols interference (ISI), the computational complexity will be unaffordable (i.e., matrix operators for nano-machines is challenging [10]). Last but not least, such linear processing schemes usually require high signal to noise ratios (SNR) to achieve the desired performance, which become impractical in noisy biological environments (constant molecular signaling from multiple sources [7], [21]).…”