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Recent works have identified hybrid analog-digital processing as a cost-effective alternative to conventional full-digital processing in massive multiple-input multiple-output (MIMO) systems owing to the deployment of far less number of radio frequency (RF) chains. In this paper, we analyze the impact of oscillator phase noise on hybrid precoding in massive MIMO systems. Relying on the time division...
In this paper, a novel pilot extension scheme is proposed for massive MIMO uplink transmission, and its performance is evaluated analytically. Specifically, we divide the cell users into two groups, namely near users and far users, according to their distances to the service base stations. The far users are more motivated to mitigate the inter-cell interference than the near users at the price of...
We consider wireless information and power transfer in a multi-user massive multiple-input multiple-output (MU-Massive-MIMO) system, where several distributed antenna sets, also denoted as remote radio heads (RRHs), are deployed, while the users can simultaneously perform information detection and energy harvesting. Assuming a large number of antennas and autonomous power allocation for the information...
A random-vector-based beamforming scheme for Millimeter-Wave (mm-Wave) MIMO systems with asymptotic optimal performance at low signal-to-noise ratio (SNR) is proposed in this paper. Through transmitting random vectors from transmitter (TX) to receiver (RX) then back to TX, the proposed scheme can obtain the estimation of channel auto-correlation with low complexity operations and then obtain the nearly...
Future mobile radio systems, like 5G, are setting extremely demanding targets with respect to the number of served users, data rates, and latency etc. Advanced techniques such as massive MIMO and joint cooperation over several distributed radio stations are being developed to achieve these targets. Channel prediction has been deemed to be a potential main enabler for these techniques. Here, we exploit...
In this paper, we analyze the performance of the fractional pilot reuse (FPR) scheme with pilot contamination mitigation in massive multiple-input multiple-output (MIMO) system. In FPR, users are classified into the cell- center and the cell-edge ones according to their signal-to- interference-plus-noise ratios (SINRs) at the receiver side. Then, the cell- edge users with low SINRs in different cells...
IEEE 802.11n/ac wireless local area network (WLAN) supports frame aggregation, called aggregate medium access control (MAC) protocol data unit (A-MPDU), to enhance MAC efficiency by reducing protocol overhead. However, the current channel estimation process conducted only once during the preamble reception is known to be insufficient to ensure robust delivery of long A-MPDU frames in mobile environments...
In this paper, we analyze the performance of multi-cell least-square (LS) channel estimation using pilot sequence hopping and pilot reuse strategy for pilot decontamination. We obtain achievable rates in uplink synchronous system in L-cell system using LS channel estimation and zero forcing (ZF) detection. Polynomial expansion approximation is performed to obtain a closed form bound of the asymptotic...
Recent work has proposed the integer-forcing (IF) linear receiver architecture as a promising alternative to the joint maximum likelihood (ML) receiver. It has been proven that the IF linear receiver can operate very close to the (optimal) performance of the joint ML receiver, but with essentially the same implementation complexity as a zero-forcing (ZF) linear receiver. In this paper, we take the...
Massive MIMO (multiple-input multiple-output) provides great improvements in spectral efficiency over legacy cellular networks, by coherent combining of the signals over a large antenna array and by spatial multiplexing of many users. Since its inception, the coherent interference caused by pilot contamination has been believed to be an impairment that does not vanish, even with an unlimited number...
This paper develops a novel channel estimation approach for multi-user millimeter wave (mmWave) wireless systems with large antenna arrays. By exploiting the inherent mmWave channel sparsity, we propose a novel simultaneous-estimation with iterative fountain training (SWIFT) framework, in which the average number of channel measurements is adapted to various channel conditions. To this end, the base...
This paper presents a modified MMSE channel estimation for turbo equalization in uplink massive multiple-input multiple-output (MIMO) systems with pilot contamination. Unlike other work on channel estimation in massive MIMO systems where perfect knowledge of inter-cell large scale channel coefficients is assumed, a modified method for data-aided MMSE estimation is proposed without requiring the knowledge...
MIMO beamforming provides high throughput for WiFi networks, but it also leads to high computation and communication overhead due to Channel State Information (CSI) feedback. Explicit CSI feedback provides high beamforming gains, but it introduces extremely high overhead. Implicit CSI feedback has low overhead, but it provides very low beamforming gains. We propose EliMO to completely Eliminate CSI...
In massive multiple-input multiple-output (MIMO) systems, superimposed (SP) and time-multiplexed (TM) pilots exhibit a complementary behavior, with the former and latter schemes offering a higher throughput in high and low inter-cell interference scenarios, respectively. Based on this observation, in this paper, we propose an algorithm for partitioning users into two disjoint sets comprising users...
The performance of multiuser multiple input multiple output (MIMO) downlink communication system is degraded under the assumption of rapid movement of user terminals with a certain speed. Though several methods have been proposed to improve this situation, they consume extra-degrees of freedom for the extension of the zero forcing (ZF) area and/or heavy computational load for the frequent update of...
In this paper, we have presented novel channel estimation technique of MIMO-OFDM system based on Extended Kalman filter. The proposed channel estimation method improves the bit error rate performance compare to conventional channel estimation method. We have also compared the proposed method with the conventional method. We have compared the Extended Kalman filter (EKF) method with the first order...
In this paper, an efficient approach is proposed to track the double-selected multipath channel for a Multiple-Input-Multiple-Output Orthogonal-Frequency-Division-Multiplexing (MIMO-OFDM) system in the existence of both Gaussian and non-Gaussian noises interfering with reference signals. Using nonlinear complex Multiple Support Vector Machine Regression (M-SVR) methodology, fast-fading multipath channel...
In this paper the impact of exponential correlation model on massive multiple input multiple output (MIMO) channel estimation is analyzed using a large number of antennas in the base station (BS) and a user terminal. We consider pilot-based channel estimation in the UL channel. The Linear minimum mean square error (LMMSE) estimator is used to investigate the effect of correlation factor on the average...
In this paper, we analyze the downlink (DL) performance of superimposed pilots in time division duplexing massive multiple-input multiple-output (MIMO) systems, and show that superimposed pilots offer an increased resilience to pilot contamination with respect to time-multiplexed pilots and data. Based on a closed form expression for the DL signal-to-interference-plus-noise ratio (SINR) at the user...
This paper considers training-based transmissions in massive multi-input multi-output (MIMO) systems with one-bit analog-to-digital converters (ADCs). We assume that each coherent transmission block consists of a pilot training stage and a data transmission stage. The base station (BS) first employs the linear minimum mean-square-error (LMMSE) method to estimate the channel and then uses the maximum-ratio...
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