88 research outputs found

    Linear Precoding with Low-Resolution DACs for Massive MU-MIMO-OFDM Downlink

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    We consider the downlink of a massive multiuser (MU) multiple-input multiple-output (MIMO) system in which the base station (BS) is equipped with low-resolution digital-to-analog converters (DACs). In contrast to most existing results, we assume that the system operates over a frequency-selective wideband channel and uses orthogonal frequency division multiplexing (OFDM) to simplify equalization at the user equipments (UEs). Furthermore, we consider the practically relevant case of oversampling DACs. We theoretically analyze the uncoded bit error rate (BER) performance with linear precoders (e.g., zero forcing) and quadrature phase-shift keying using Bussgang's theorem. We also develop a lower bound on the information-theoretic sum-rate throughput achievable with Gaussian inputs, which can be evaluated in closed form for the case of 1-bit DACs. For the case of multi-bit DACs, we derive approximate, yet accurate, expressions for the distortion caused by low-precision DACs, which can be used to establish lower bounds on the corresponding sum-rate throughput. Our results demonstrate that, for a massive MU-MIMO-OFDM system with a 128-antenna BS serving 16 UEs, only 3--4 DAC bits are required to achieve an uncoded BER of 10^-4 with a negligible performance loss compared to the infinite-resolution case at the cost of additional out-of-band emissions. Furthermore, our results highlight the importance of taking into account the inherent spatial and temporal correlations caused by low-precision DACs

    Massive MU-MIMO-OFDM Downlink with One-Bit DACs and Linear Precoding

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    Massive multiuser (MU) multiple-input multiple- output (MIMO) is foreseen to be a key technology in future wireless communication systems. In this paper, we analyze the downlink performance of an orthogonal frequency division multiplexing (OFDM)-based massive MU-MIMO system in which the base station (BS) is equipped with 1-bit digital-to-analog converters (DACs). Using Bussgang's theorem, we characterize the performance achievable with linear precoders (such as maximal-ratio transmission and zero forcing) in terms of bit error rate (BER). Our analysis accounts for the possibility of oversampling the time-domain transmit signal before the DACs. We further develop a lower bound on the information-theoretic sum-rate throughput achievable with Gaussian inputs. Our results suggest that the performance achievable with 1-bit DACs in a massive MU-MIMO-OFDM downlink are satisfactory provided that the number of BS antennas is sufficiently large

    On Out-of-Band Emissions of Quantized Precoding in Massive MU-MIMO-OFDM

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    We analyze out-of-band (OOB) emissions in the massive multi-user (MU) multiple-input multiple-output (MIMO) downlink. We focus on systems in which the base station (BS) is equipped with low-resolution digital-to-analog converters (DACs) and orthogonal frequency-division multiplexing (OFDM) is used to communicate to the user equipments (UEs) over frequency-selective channels. We demonstrate that analog filtering in combination with simple frequency-domain digital predistortion (DPD) at the BS enables a significant reduction of OOB emissions, but degrades the signal-to-interference-noise-and-distortion ratio (SINDR) at the UEs and increases the peak-to-average power ratio (PAR) at the BS. We use Bussgang's theorem to characterize the tradeoffs between OOB emissions, SINDR, and PAR, and to study the impact of analog filters and DPD on the error-rate performance of the massive MU-MIMO-OFDM downlink. Our results show that by carefully tuning the parameters of the analog filters, one can achieve a significant reduction in OOB emissions with only a moderate degradation of error-rate performance and PAR.Comment: Presented at the 2017 Asilomar Conference on Signals, Systems, and Computers, 6 page

    Impact of Residual Transmit RF Impairments on Training-Based MIMO Systems

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    Radio-frequency (RF) impairments, that exist intimately in wireless communications systems, can severely degrade the performance of traditional multiple-input multiple-output (MIMO) systems. Although compensation schemes can cancel out part of these RF impairments, there still remains a certain amount of impairments. These residual impairments have fundamental impact on the MIMO system performance. However, most of the previous works have neglected this factor. In this paper, a training-based MIMO system with residual transmit RF impairments (RTRI) is considered. In particular, we derive a new channel estimator for the proposed model, and find that RTRI can create an irreducible estimation error floor. Moreover, we show that, in the presence of RTRI, the optimal training sequence length can be larger than the number of transmit antennas, especially in the low and high signal-to-noise ratio (SNR) regimes. An increase in the proposed approximated achievable rate is also observed by adopting the optimal training sequence length. When the training and data symbol powers are required to be equal, we demonstrate that, at high SNRs, systems with RTRI demand more training, whereas at low SNRs, such demands are nearly the same for all practical levels of RTRI.Comment: Accepted for publication at the IEEE International Conference on Communications (ICC 2014), 6 pages, 5 figure

    One-Bit Massive MIMO: Channel Estimation and High-Order Modulations

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    We investigate the information-theoretic throughout achievable on a fading communication link when the receiver is equipped with one-bit analog-to-digital converters (ADCs). The analysis is conducted for the setting where neither the transmitter nor the receiver have a priori information on the realization of the fading channels. This means that channel-state information needs to be acquired at the receiver on the basis of the one-bit quantized channel outputs. We show that least-squares (LS) channel estimation combined with joint pilot and data processing is capacity achieving in the single-user, single-receive-antenna case. We also investigate the achievable uplink throughput in a massive multiple-input multiple-output system where each element of the antenna array at the receiver base-station feeds a one-bit ADC. We show that LS channel estimation and maximum-ratio combining are sufficient to support both multiuser operation and the use of high-order constellations. This holds in spite of the severe nonlinearity introduced by the one-bit ADCs

    On the MIMO Capacity with Residual Transceiver Hardware Impairments

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    Radio-frequency (RF) impairments in the transceiver hardware of communication systems (e.g., phase noise (PN), high power amplifier (HPA) nonlinearities, or in-phase/quadrature-phase (I/Q) imbalance) can severely degrade the performance of traditional multiple-input multiple-output (MIMO) systems. Although calibration algorithms can partially compensate these impairments, the remaining distortion still has substantial impact. Despite this, most prior works have not analyzed this type of distortion. In this paper, we investigate the impact of residual transceiver hardware impairments on the MIMO system performance. In particular, we consider a transceiver impairment model, which has been experimentally validated, and derive analytical ergodic capacity expressions for both exact and high signal-to-noise ratios (SNRs). We demonstrate that the capacity saturates in the high-SNR regime, thereby creating a finite capacity ceiling. We also present a linear approximation for the ergodic capacity in the low-SNR regime, and show that impairments have only a second-order impact on the capacity. Furthermore, we analyze the effect of transceiver impairments on large-scale MIMO systems; interestingly, we prove that if one increases the number of antennas at one side only, the capacity behaves similar to the finite-dimensional case. On the contrary, if the number of antennas on both sides increases with a fixed ratio, the capacity ceiling vanishes; thus, impairments cause only a bounded offset in the capacity compared to the ideal transceiver hardware case.Comment: Accepted for publication at the IEEE International Conference on Communications (ICC 2014), 7 pages, 6 figure

    Adaptive Multicell 3D Beamforming in Multi-Antenna Cellular Networks

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    We consider a cellular network with multi-antenna base stations (BSs) and single-antenna users, multicell cooperation, imperfect channel state information, and directional antennas each with a vertically adjustable beam. We investigate the impact of the elevation angle of the BS antenna pattern, denoted as tilt, on the performance of the considered network when employing either a conventional single-cell transmission or a fully cooperative multicell transmission. Using the results of this investigation, we propose a novel hybrid multicell cooperation technique in which the intercell interference is controlled via either cooperative beamforming in the horizontal plane or coordinated beamfroming in the vertical plane of the wireless channel, denoted as adaptive multicell 3D beamforming. The main idea is to divide the coverage area into two disjoint vertical regions and adapt the multicell cooperation strategy at the BSs when serving each region. A fair scheduler is used to share the time-slots between the vertical regions. It is shown that the proposed technique can achieve performance comparable to that of a fully cooperative transmission but with a significantly lower complexity and signaling requirements. To make the performance analysis computationally efficient, analytical expressions for the user ergodic rates under different beamforming strategies are also derived.Comment: Accepted for publication in IEEE Transaction on Vehicular Technolog

    An Efficient Signaling for Multi-mode Transmission in Multi-user MIMO

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    In this paper the downlink of a multi-user MIMO (MUMIMO) system with multi-mode transmission is considered. We propose a low-complexity algorithm for selecting users and the corresponding number of data streams to each user, denoted as user transmission mode (UTM). The selection is only based on the average received signal-to-noise ratio (SNR) from the base station (BS) for each user. This reduces the overall amount of feedback for scheduling, as opposed to techniques that assume perfect instantaneous channel state information (CSI) from all users. Analytical average throughput approximations are derived for each user at different UTMs. Simulation results demonstrate that the proposed algorithm provides performance close to dirty paper coding (DPC) with considerably reduced feedback

    Shannon Capacity of LOS MIMO Channels with Uniform Circular Arrays

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    The Shannon capacity for the line-of-sight (LOS) multiple-input multiple-output (MIMO) channel between two perfectly aligned uniform circular arrays (UCAs) is derived from the first principles in a tutorial fashion. It is well known that harmonically related complex exponentials (also known in the literature as orbital angular momentum (OAM) modes) are eigenmodes for the spatially continuous channel. We show that the corresponding eigenvalues can be expressed as Bessel functions of the first kind. We also show that the spatially discrete channel between two UCAs with the same finite number of Hertzian dipole antennas on both sides has eigenmodes that are spatially sampled continuous OAM modes, and discrete eigenvalues that are aliased versions of the continuous eigenvalues. Through numerical solution of Maxwell\u27s equations, we verify that the discrete eigenvalues for UCAs with realistic dipole antennas are the same as with the Hertzian dipoles for the studied geometries (1~km hop distance, UCA radius 1 and 2 m, carrier frequency 70 GHz) as long as antenna spacing is not very dense

    Distributed Massive MIMO via all-Digital Radio Over Fiber

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    A crucial challenge in the implementation of distributed massive multiple-input multiple-output (MIMO) architectures is to provide phase coherence while, at the same time, limit the complexity of the remote-radio heads (RRHs), which is important for cost-efficient scalability. To address this challenge, we present in this paper a phase-coherent distributed MIMO architecture, based on off-the-shelf, low-cost components. In the proposed architecture, up- and down-conversion are carried out at the central unit (CU). The RRHs are connected to the CU by means of optical fibers carrying oversampled radio-frequency (RF) 1-bit signals. In the downlink, the 1-bit signal is generated via sigma-delta modulation. At the RRH, the RF signal is recovered from the 1-bit signal through a bandpass filter and a power amplifier, and then fed to an antenna. In the uplink, the 1-bit signal is generated by a comparator whose inputs are the low-noise-amplified received RF signal and a suitably designed dither signal. The performance of the proposed architecture is evaluated with satisfactory results both via simulation and measurements from a testbed
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