
arXiv: 1501.05371
AbstractIn a multistatic cloud radar system, receive sensors measure signals sent by a transmit element and reflected from a target and possibly clutter, in the presence of interference and noise. The receive sensors communicate over non‐ideal backhaul links with a fusion center, or cloud processor, where the presence or absence of the target is determined. The backhaul architecture can be characterized either by an orthogonal‐access channel or by a non‐orthogonal multiple‐access channel. Two backhaul transmission strategies are considered, namely, compress‐and‐forward (CF), which is well suited for the orthogonal‐access backhaul, and amplify‐and‐forward (AF), which leverages the superposition property of the non‐orthogonal multiple‐access channel. In this paper, thejointoptimization of the sensing and backhaul communication functions of the cloud radar system is studied. Specifically, the transmitted waveform is jointly optimized with backhaul quantization in the case of CF backhaul transmission and with the amplifying gains of the sensors for the AF backhaul strategy. In both cases, the information‐theoretic criterion of the Bhattacharyya distance is adopted as a metric for the detection performance. Algorithmic solutions based on successive convex approximation are developed under different assumptions on the available channel state information. Numerical results demonstrate that the proposed schemes outperform conventional solutions that performseparateoptimizations of the waveform and backhaul operation, as well as the standard distributed detection approach. Copyright © 2016 John Wiley & Sons, Ltd.
FOS: Computer and information sciences, Computer Science - Information Theory, Information Theory (cs.IT)
FOS: Computer and information sciences, Computer Science - Information Theory, Information Theory (cs.IT)
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 12 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
