857 research outputs found

    Impact of Line-of-Sight and Unequal Spatial Correlation on Uplink MU-MIMO Systems

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    Closed-form approximations of the expected per-terminal signal-to-interference-plus-noise-ratio (SINR) and ergodic sum spectral efficiency of a multiuser multiple-input multiple-output system are presented. Our analysis assumes spatially correlated Ricean fading channels with maximum-ratio combining on the uplink. Unlike previous studies, our model accounts for the presence of unequal correlation matrices, unequal Rice factors, as well as unequal link gains to each terminal. The derived approximations lend themselves to useful insights, special cases and demonstrate the aggregate impact of line-of-sight (LoS) and unequal correlation matrices. Numerical results show that while unequal correlation matrices enhance the expected SINR and ergodic sum spectral efficiency, the presence of strong LoS has an opposite effect. Our approximations are general and remain insensitive to changes in the system dimensions, signal-to-noise-ratios, LoS levels and unequal correlation levels.Comment: 4 pages, 2 figures, accepted for publication in the IEEE Wireless Communications Letters, Vol. 6, 201

    Uplink Analysis of Large MU-MIMO Systems With Space-Constrained Arrays in Ricean Fading

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    Closed-form approximations to the expected per-terminal signal-to-interference-plus-noise-ratio (SINR) and ergodic sum spectral efficiency of a large multiuser multiple-input multiple-output system are presented. Our analysis assumes correlated Ricean fading with maximum ratio combining on the uplink, where the base station (BS) is equipped with a uniform linear array (ULA) with physical size restrictions. Unlike previous studies, our model caters for the presence of unequal correlation matrices and unequal Rice factors for each terminal. As the number of BS antennas grows without bound, with a finite number of terminals, we derive the limiting expected per-terminal SINR and ergodic sum spectral efficiency of the system. Our findings suggest that with restrictions on the size of the ULA, the expected SINR saturates with increasing operating signal-to-noise-ratio (SNR) and BS antennas. Whilst unequal correlation matrices result in higher performance, the presence of strong line-of-sight (LoS) has an opposite effect. Our analysis accommodates changes in system dimensions, SNR, LoS levels, spatial correlation levels and variations in fixed physical spacings of the BS array.Comment: 7 pages, 3 figures, accepted for publication in the proceedings of IEEE ICC, to be held in Paris, France, May 201

    A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles

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    In recent years, there has been a dramatic increase in the use of unmanned aerial vehicles (UAVs), particularly for small UAVs, due to their affordable prices, ease of availability, and ease of operability. Existing and future applications of UAVs include remote surveillance and monitoring, relief operations, package delivery, and communication backhaul infrastructure. Additionally, UAVs are envisioned as an important component of 5G wireless technology and beyond. The unique application scenarios for UAVs necessitate accurate air-to-ground (AG) propagation channel models for designing and evaluating UAV communication links for control/non-payload as well as payload data transmissions. These AG propagation models have not been investigated in detail when compared to terrestrial propagation models. In this paper, a comprehensive survey is provided on available AG channel measurement campaigns, large and small scale fading channel models, their limitations, and future research directions for UAV communication scenarios

    Dual-Polarized Ricean MIMO Channels: Modeling and Performance Assessment

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    In wireless communication systems, dual-polarized (DP) instead of single-polarized (SP) multiple-input multiple-output (MIMO) transmission is used to improve the spectral efficiency under certain conditions on the channel and the signal-to-noise ratio (SNR). In order to identify these conditions, we first propose a novel channel model for DP mobile Ricean MIMO channels for which statistical channel parameters are readily obtained from a moment-based channel decomposition. Second, we derive an approximation of the mutual information (MI), which can be expressed as a function of those statistical channel parameters. Based on this approximation, we characterize the required SNR for a DP MIMO system to outperform an SP MIMO system in terms of the MI. Finally, we apply our results to channel measurements at 2.53 GHz. We find that, using the proposed channel decomposition and the approximation of the MI, we are able to reproduce the (practically relevant) SNR values above which DP MIMO systems outperform SP MIMO systems.Comment: submitted to the IEEE Transactions on Communication

    Distributed Detection over Fading MACs with Multiple Antennas at the Fusion Center

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    A distributed detection problem over fading Gaussian multiple-access channels is considered. Sensors observe a phenomenon and transmit their observations to a fusion center using the amplify and forward scheme. The fusion center has multiple antennas with different channel models considered between the sensors and the fusion center, and different cases of channel state information are assumed at the sensors. The performance is evaluated in terms of the error exponent for each of these cases, where the effect of multiple antennas at the fusion center is studied. It is shown that for zero-mean channels between the sensors and the fusion center when there is no channel information at the sensors, arbitrarily large gains in the error exponent can be obtained with sufficient increase in the number of antennas at the fusion center. In stark contrast, when there is channel information at the sensors, the gain in error exponent due to having multiple antennas at the fusion center is shown to be no more than a factor of (8/pi) for Rayleigh fading channels between the sensors and the fusion center, independent of the number of antennas at the fusion center, or correlation among noise samples across sensors. Scaling laws for such gains are also provided when both sensors and antennas are increased simultaneously. Simple practical schemes and a numerical method using semidefinite relaxation techniques are presented that utilize the limited possible gains available. Simulations are used to establish the accuracy of the results.Comment: 21 pages, 9 figures, submitted to the IEEE Transactions on Signal Processin

    Does Massive MIMO Fail in Ricean Channels?

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    Massive multiple-input multiple-output (MIMO) is now making its way to the standardization exercise of future 5G networks. Yet, there are still fundamental questions pertaining to the robustness of massive MIMO against physically detrimental propagation conditions. On these grounds, we identify scenarios under which massive MIMO can potentially fail in Ricean channels, and characterize them physically, as well as, mathematically. Our analysis extends and generalizes a stream of recent papers on this topic and articulates emphatically that such harmful scenarios in Ricean fading conditions are unlikely and can be compensated using any standard scheduling scheme. This implies that massive MIMO is intrinsically effective at combating interuser interference and, if needed, can avail of the base-station scheduler for further robustness.Comment: IEEE Wireless Communications Letters, accepte

    A Simple Cooperative Diversity Method Based on Network Path Selection

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    Cooperative diversity has been recently proposed as a way to form virtual antenna arrays that provide dramatic gains in slow fading wireless environments. However most of the proposed solutions require distributed space-time coding algorithms, the careful design of which is left for future investigation if there is more than one cooperative relay. We propose a novel scheme, that alleviates these problems and provides diversity gains on the order of the number of relays in the network. Our scheme first selects the best relay from a set of M available relays and then uses this best relay for cooperation between the source and the destination. We develop and analyze a distributed method to select the best relay that requires no topology information and is based on local measurements of the instantaneous channel conditions. This method also requires no explicit communication among the relays. The success (or failure) to select the best available path depends on the statistics of the wireless channel, and a methodology to evaluate performance for any kind of wireless channel statistics, is provided. Information theoretic analysis of outage probability shows that our scheme achieves the same diversity-multiplexing tradeoff as achieved by more complex protocols, where coordination and distributed space-time coding for M nodes is required, such as those proposed in [7]. The simplicity of the technique, allows for immediate implementation in existing radio hardware and its adoption could provide for improved flexibility, reliability and efficiency in future 4G wireless systems.Comment: To appear, IEEE JSAC, special issue on 4

    Maximum likelihood receivers for space-time coded MIMO systems with gaussian estimation errors

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    Maximum likelihood (ML) receivers for space-time coded multiple-input multiple-output (MIMO) systems with Gaussian channel estimation errors are proposed. Two different cases are considered. In the first case, the conditional probability density function (PDF) of the channel estimate is assumed Gaussian and known. In the second case, the joint PDF of the channel estimate and the true channel gain is assumed Gaussian and known. In addition to ML signal detection for space-time coded MIMO with ML and minimum mean-squared-error channel estimation, ML signal detection without channel estimation is also studied. Two suboptimal structures are derived. The Alamouti space-time codes are used to examine the performances of the new receivers. Simulation results show that the new receivers can reduce the gap between the conventional receiver with channel estimation errors and the receiver with perfect channel knowledge at least by half in some cases
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