1,720,964 research outputs found
Asymptotically Optimal Simple User Scheduling for Massive MIMO Downlink with Two-Stage Beamforming
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On the performance of randomly directional beamforming between line-of-sight and rich scattering channels
No full textUser Scheduling for Millimeter Wave Hybrid Beamforming Systems With Low-Resolution ADCs
No full textWe investigate uplink user scheduling for millimeter wave (mm-wave) hybrid analog/digital beamforming systems with low-resolution analog-to-digital converters (ADCs). Deriving new scheduling criteria for the mm-wave systems, we show that the channel structure in the beamspace, in addition to the channel magnitude and orthogonality, plays a key role in maximizing the achievable rates of scheduled users due to quantization error. The criteria show that to maximize the achievable rate for a given channel gain, the channels of the scheduled users need to have 1) as many propagation paths as possible with unique angle-ofarrivals (AoAs) and 2) even power distribution in the beamspace. Leveraging the derived criteria, we propose an efficient scheduling algorithm for mm-wave zero-forcing receivers with low-resolution ADCs. We further propose a chordal distance-based scheduling algorithm that exploits only the AoA knowledge and analyze the performance by deriving ergodic rates in closed form. Based on the derived rates, we show that the beamspace channel leakage resulting from phase offsets between AoAs and quantized angles of analog combiners can lead to sum rate gain by reducing quantization error compared to the channel without leakage. The simulation results validate the sum rate performance of the proposed algorithms and the derived ergodic rate expressions
Two-Stage Analog Combining in Hybrid Beamforming Systems With Low-Resolution ADCs
No full textIn this paper, we investigate hybrid analog/digital beamforming for multiple-input multiple-output (MIMO) systems with low-resolution analog-to-digital converters for millimeter wave (mmWave) communications. In the receiver, we propose to split the analog combining subsystem into a channel gain aggregation stage followed by a spreading stage. Both stages use phase shifters. Our goal is to design the two-stage analog combiner to optimize mutual information (MI) between the transmitted and quantized signals by effectively managing quantization error. To this end, we formulate an unconstrained MI maximization problem without a constant modulus constraint on analog combiners, and derive a two-stage analog combining solution. The solution achieves the optimal scaling law with respect to the number of radio frequency chains and maximizes the MI for homogeneous singular values of a MIMO channel. We further develop a two-stage analog combining algorithm to implement the derived solution for mmWave channels. By decoupling channel gain aggregation and spreading functions from the derived solution, the proposed algorithm implements the two functions by using array response vectors and a discrete Fourier transform matrix under the constant modulus constraint on each matrix element. Therefore, the proposed algorithm provides a near-optimal solution for the unconstrained problem, whereas conventional hybrid approaches offer a near optimal solution only for a constrained problem. The closed-form approximation of the ergodic rate is derived for the algorithm, showing that a practical digital combiner with two-stage analog combining also achieves the optimal scaling law. Simulation results validate the algorithm performance and the derived ergodic rate
Pilot beam sequence design for channel estimation in millimeter-wave MIMO systems: A POMDP framework
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Advanced Receiver Architectures for Millimeter-Wave Communications with Low-Resolution ADCs
No full textEmploying low-resolution analog-to-digital converters (ADCs) for millimeter-wave receivers with large antenna arrays provides an opportunity to efficiently reduce power consumption of the receiver. Reducing ADC resolution, however, results in performance degradation due to non-negligible quantization error. In addition, the large number of radio frequency chains is still not desirable. Accordingly, conventional low-resolution ADC systems require more efficient designs to minimize the cost and complexity while maximizing performance. In this article, we discuss advanced low-resolution ADC receiver architectures that further improve the spectral and energy efficiency trade-off. To reduce both the numbers of RF chains and ADC bits, hybrid analog and digital beamforming is jointly considered with low-resolution ADCs. We explore the challenges in designing such receivers and present key insights on how the advanced architectures overcome such challenges. As alternative low-resolution ADC receivers, we also introduce receivers with learning-based detection. The receiver does not require explicit channel estimation, and thus is suitable for one-bit ADC systems. Finally, future challenges and research issues are discussed. ?? 1979-2012 IEEE
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