The characteristics of wireless communication channels may vary with time due to fading, environmental changes and movement of mobile wireless devices. Tracking and estimating channel gains of wireless channels is therefore a fundamentally important element of many wireless communication systems. In particular, the receivers in many wireless networks need to estimate the channel gains by means of a training sequence. This paper studies the scaling law (on the network size) of the overhead for channel gain monitoring in wireless network. We first investigate the scenario in which a receiver needs to track the channel gains with respect to multiple transmitters. To be concrete, suppose that there are n transmitters, and that in the current round of channel-gain estimation, no more than k channels suffer significant variations since the last round. We proves that " (k ((n+1) k)) time slots" is the minimum number of time slots needed to catch up with the k varied channels. At the same time, we propose a novel channel-gain monitoring scheme named ADMOT to achieve the overhead lower-bound. ADMOT leverages recent advances in compressive sensing in signal processing and interference processing in wireless communication, to enable the receiver to estimate all n channels in a reliable and computationally efficient manner within O(k ((n+1) k)) time slots. To our best knowledge, all previous channel-tracking schemes require (n) time slots regardless of k. Note that based on above results for single receiver scenario, the scaling law of general setting is achieved in which there are multiple transmitters, relay nodes and receivers.
Note that some previous schemes mentioned above estimate the property of a wideband channel, in which the channel gain varies across the frequency within the channel bandwidth. In contrast, this paper investigates the scaling law (on the network size) of wireless network monitoring. For the sake of exposition, we focus on narrowband channels in which the channel gain is flat across the bandwidth of the channel. We believe that within the same scaling law complexity, ADMOT can easily be generalized to OFDM systems @cite_22 , in which information is carried across multiple narrowband channels.
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1. Introduction 2. The wireless channel 3. Point-to-point communication: detection, diversity and channel uncertainty 4. Cellular systems: multiple access and interference management 5. Capacity of wireless channels 6. Multiuser capacity and opportunistic communication 7. MIMO I: spatial multiplexing and channel modeling 8. MIMO II: capacity and multiplexing architectures 9. MIMO III: diversity-multiplexing tradeoff and universal space-time codes 10. MIMO IV: multiuser communication A. Detection and estimation in additive Gaussian noise B. Information theory background.