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.
@cite_22
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We consider a single cell wireless uplink in which randomly arriving devices transmit their payload to a receiver. Given SNR per user, payload size per device, a fixed latency constraint T, total available bandwidth W, i.e., total symbol resources is given by N = TW. The total bandwidth W is evenly partitioned into B bins. Each time slot of duration T is split into a maximum number of retransmission attempts M. Hence, the N resources are partitioned into N MB resources each bin per retransmission. We characterize the maximum average rate or number of Poisson arrivals that can successfully complete the random access procedure such that the probability of outage is sufficiently small. We analyze the proposed setting for i) noise-limited regime and ii) interference-limited regime. We show that in the noise-limited regime the devices share the resources, and in the interference-limited regime, the resources split such that devices do not experience any interference. We then incorporate Rayleigh fading to model the channel power gain distribution. Although the variability of the channel causes a drop in the number of arrivals that can successfully complete the random access phase, similar scaling results extend to the Rayleigh fading case. We investigate distributed beamforming from a cluster of N cooperating transmitters to a distant destination over a wideband dispersive channel. Feedback from the destination is critical for enabling this. In order to develop protocols that scale to arbitrarily large numbers of cooperating nodes, we restrict attention to aggregate feedback broadcast from the destination to the entire transmit cluster, rather than per-transmitter channel feedback as in conventional feedback-based MIMO systems. We first show that naive application of a one-bit feedback algorithm developed for narrowband channels to each subcarrier in an OFDM system does achieve beamforming gain on each subcarrier, but results in an effective channel at the destination with severe phase discontinuities across frequency, which is not amenable to standard receive channel estimation algorithms. We then show that it is possible to enforce smoothness of phase across frequency by augmenting the feedback to 2 bits per subcarrier, which enables modeling and estimation of the effective channel as sparse in the time domain. Our preliminary results show that, even when the SNR per node is well below the threshold for reliable demodulation, it is possible to bootstrap using the N-fold power pooling gain obtained from incoherent combining of the signals from multiple transmitters, and to attain a significant fraction of the N2-fold beamforming gain using the proposed algorithm. We also discuss a number of open issues, recognizing that this is only a first step in developing scalable, wideband, distributed MIMO systems. This paper presents the channel measurements performed within a closed met al cabinet at 60 GHz covering the frequency range 57–62 GHz. Two different volumes of an empty met al cupboard are considered to emulate the environment of interest (an industrial machine). Furthermore, we have considered a number of scenarios such as line of sight, non line of sight, and placing absorbers. A statistical channel model is provided to aid short-range wireless link design within such a reflective and confined environment. Based on the measurements, the large- and small-scale parameters are extracted and fitted using the standard log-normal and Saleh–Valenzuela models, respectively. The obtained results are characterized by a very small path loss exponent, a single cluster phenomenon, and a significantly large root-mean-square (RMS) delay spread. The results show that covering a wall with absorber material dramatically reduces the RMS delay spread. Finally, the proposed channel model is validated by comparing the measured channel with a simulated channel, where the simulated channel is generated from the extracted parameters. In millimeter wave (mm-wave) massive multiple-input multiple-output (MIMO) systems, acquiring accurate channel state information is essential for efficient beamforming (BF) and multiuser interference cancellation, which is a challenging task since a low signal-to-noise ratio is encountered before BF in large antenna arrays. The mm-wave channel exhibits a 3-D clustered structure in the virtual angle of arrival (AOA), angle of departure (AOD), and delay domain that is imposed by the effect of power leakage, angular spread, and cluster duration. We extend the approximate message passing (AMP) with a nearest neighbor pattern learning algorithm for improving the attainable channel estimation performance, which adaptively learns and exploits the clustered structure in the 3-D virtual AOA-AOD-delay domain. The proposed method is capable of approaching the performance bound described by the state evolution based on vector AMP framework, and our simulation results verify its superiority in mm-wave systems associated with a broad bandwidth.