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Saif Khan Mohammed

Publications and source records attributed to Saif Khan Mohammed.

51 records · Page 3Linked to original sources

Impact of CFO Estimation on the Performance of ZF Receiver in Massive MU-MIMO Systems

In this paper, we study the impact of carrier frequency offset (CFO) estimation/compensation on the information rate performance of the zero-forcing (ZF) receiver in the uplink of a multi-user massive multiple-input multiple-output (MIMO) system. Analysis of the derived closed-form expression of the per-user information rate reveals that with increasing number of BS antennas $M$, an $\mathcal{O}(\sqrt{M})$ array gain is achievable, which is same as that achieved in the ideal zero CFO scenario. Also it is observed that compared to the ideal zero CFO case, the performance degradation in the presence of residual CFO (after CFO compensation) is the same for both ZF and MRC.

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Low-Complexity CFO Estimation for Multi-User Massive MIMO Systems

Low-complexity carrier frequency offset (CFO) estimation and compensation in multi-user massive multiple-input multiple-output (MIMO) systems is a challenging problem. The existing CFO estimation algorithms incur tremendous increase in complexity with increasing number of base station (BS) antennas, $M$ and number of user terminals (UTs) $K$ (i.e. massive MIMO regime). In this paper, we address this problem by proposing a novel low-complexity algorithm for CFO estimation which uses the pilot signal received at the BS during special uplink slots. The total per-channel use complexity of the proposed algorithm increases only linearly with increasing $M$ and is independent of $K$. Analysis reveals that the CFO estimation accuracy can be considerably improved by increasing $M$ and $K$ (i.e. massive MIMO regime). For example, for a fixed $K$ and a fixed training length, the required per-user radiated power during uplink training decreases as $\frac{1}{\sqrt{M}}$ with increasing $M$.

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Constant-Envelope Precoding with Time-Variation Constraint on the Transmitted Phase Angles

We consider downlink precoding in a frequency-selective multi-user massive MIMO system with highly efficient but non-linear power amplifiers at the base station (BS). A low-complexity precoding algorithm is proposed, which generates constant-envelope (CE) transmit signals for each BS antenna. To avoid large variations in the phase angle transmitted from each antenna, the difference of the phase angles transmitted in consecutive channel uses is limited to $[-απ\,,\, απ]$ for a fixed $0 < α\leq 1$. To achieve a desired per-user information rate, the extra total transmit power required under the time variation constraint when compared to the special case of no time variation constraint (i.e., $α=1$), is small for many practical values of $α$. In a i.i.d. Rayleigh fading channel with $80$ BS antennas, $5$ single-antenna users and a desired per-user information rate of $1$ bit-per-channel-use, the extra total transmit power required is less than $2.0$ dB when $α= 1/2$.

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Improving the Performance of the Zero-Forcing Multiuser MISO Downlink Precoder through User Grouping

We consider the Multiple Input Single Output (MISO) Gaussian Broadcast channel with $N_t$ antennas at the base station (BS) and $N_u$ single-antenna users in the downlink. We propose a novel user grouping precoder which improves the sum rate performance of the Zero-Forcing (ZF) precoder specially when the channel is ill-conditioned. The proposed precoder partitions all the users into small groups of equal size. Downlink beamforming is then done in such a way that, at each user's receiver the interference from the signal intended for users not in its group is nulled out. Intra-group interference still remains, and is cancelled through successive interference pre-subtraction at the BS using Dirty Paper Coding (DPC). The proposed user grouping method is different from user selection, since it is a method for precoding of information to the selected (scheduled) users, and not for selecting which users are to be scheduled. Through analysis and simulations, the proposed user grouping based precoder is shown to achieve significant improvement in the achievable sum rate when compared to the ZF precoder. When users are paired (i.e., each group has two users), the complexity of the proposed precoder is $O(N_u^3) + O(N_u^2 N_t)$ which is the same as that of the ZF precoder.

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Impact of Transceiver Power Consumption on the Energy Efficiency of Zero-Forcing Detector in Massive MIMO Systems

We consider the impact of transceiver power consumption on the energy efficiency (EE) of the Zero Forcing (ZF) detector in the uplink of massive MIMO systems, where a base station (BS) with $M$ antennas communicates coherently with $K$ single antenna user terminals (UTs). We consider the problem of maximizing the EE with respect to (M,K) for a fixed sum spectral efficiency. Through analysis we study the impact of system parameters on the optimal EE. System parameters consists of the average channel gain to the users and the power consumption parameters (PCPs) (e.g., power consumed by each RF antenna/receiver at BS). When the average user channel gain is high or else the BS/UT design is power inefficient, our analysis reveals that it is optimal to have a few BS antennas and a single user, i.e., non-massive MIMO regime. Similarly, when the channel gain is small or else the BS/UT design is power efficient, it is optimal of have a larger (M,K), i.e., massive MIMO regime. Tight analytical bounds on the optimal EE are proposed for both these regimes. The impact of the system parameters on the optimal EE is studied and several interesting insights are drawn.

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Energy-Spectral Efficiency Trade-off for a Massive SU-MIMO System with Transceiver Power Consumption

We consider a single user (SU) massive MIMO system with multiple antennas at the transmitter (base station) and a single antenna at the user terminal (UT). Taking transceiver power consumption into consideration, for a given spectral efficiency (SE) we maximize the energy efficiency (EE) as a function of the number of base station (BS) antennas $M$, resulting in a closed-form expression for the optimal SE-EE trade-off. It is observed that in contrast to the classical SE-EE trade-off (which considers only the radiated power), with transceiver power consumption taken into account, the EE increases with increasing SE when SE is sufficiently small. Further, for a fixed SE we analyze the impact of varying cell size (i.e., equivalently average channel gain $G_c$) on the optimal EE. We show the interesting result that for sufficiently small $G_c$, the optimal EE decreases as $\mathcal{O}(\sqrt{G_c})$ with decreasing $G_c$. Our analysis also reveals that for sufficiently small SE (or large $G_c$), the EE is insensitive to the power amplifier efficiency.

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Uplink Performance of Time-Reversal MRC in Massive MIMO Systems Subject to Phase Noise

Multi-user multiple-input multiple-output (MU-MIMO) cellular systems with an excess of base station (BS) antennas (Massive MIMO) offer unprecedented multiplexing gains and radiated energy efficiency. Oscillator phase noise is introduced in the transmitter and receiver radio frequency chains and severely degrades the performance of communication systems. We study the effect of oscillator phase noise in frequency-selective Massive MIMO systems with imperfect channel state information (CSI). In particular, we consider two distinct operation modes, namely when the phase noise processes at the $M$ BS antennas are identical (synchronous operation) and when they are independent (non-synchronous operation). We analyze a linear and low-complexity time-reversal maximum-ratio combining (TR-MRC) reception strategy. For both operation modes we derive a lower bound on the sum-capacity and we compare their performance. Based on the derived achievable sum-rates, we show that with the proposed receive processing an $O(\sqrt{M})$ array gain is achievable. Due to the phase noise drift the estimated effective channel becomes progressively outdated. Therefore, phase noise effectively limits the length of the interval used for data transmission and the number of scheduled users. The derived achievable rates provide insights into the optimum choice of the data interval length and the number of scheduled users.

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On the Energy-Spectral Efficiency Trade-off of the MRC Receiver in Massive MIMO Systems with Transceiver Power Consumption

We consider the uplink of a multiuser massive MIMO system wherein a base station (BS) having $M$ antennas communicates coherently with $K$ single antenna user terminals (UTs). We study the energy efficiency of this system while taking the transceiver power consumption at the UTs and the BS into consideration. For a given spectral efficiency $R$ and fixed transceiver power consumption parameters, we propose and analyze the problem of maximizing the energy efficiency as a function of $(M,K)$. For the maximum ratio combining (MRC) detector at the BS we show that with increasing $R$, $(M,K)$ can be adaptively increased in such a way that the energy efficiency converges to a positive constant as $R \rightarrow \infty$ ($(M,K)$ is increased in such a way that a constant per-user spectral efficiency $R/K$ is maintained). This is in contrast to the fixed $(M,K)$ scenario where the energy efficiency is known to converge to zero as $R \rightarrow \infty$. We also observe that for large $R$, the optimal $(M,K)$ maximizing the energy efficiency is such that, the total power consumed by the power amplifiers (PA) in all the $K$ UTs is a small fraction of the total system power consumption.

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Constant-Envelope Multi-User Precoding for Frequency-Selective Massive MIMO Systems

We consider downlink precoding in a frequency-selective multi-user Massive MIMO system with highly efficient but non-linear power amplifiers at the base station (BS). A low-complexity precoding algorithm is proposed, which generates constant-envelope (CE) signals at each BS antenna. To achieve a desired per-user information rate, the extra total transmit power required under the per-antenna CE constraint when compared to the commonly used less stringent total average transmit power constraint, is small.

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Per-antenna Constant Envelope Precoding for Large Multi-User MIMO Systems

We consider the multi-user MIMO broadcast channel with $M$ single-antenna users and $N$ transmit antennas under the constraint that each antenna emits signals having constant envelope (CE). The motivation for this is that CE signals facilitate the use of power-efficient RF power amplifiers. Analytical and numerical results show that, under certain mild conditions on the channel gains, for a fixed $M$, array gain is achievable even under the stringent per-antenna CE constraint (essentially, for a fixed $M$, at sufficiently large $N$ the total transmitted power can be reduced with increasing $N$ while maintaining a fixed information rate to each user). Simulations for the i.i.d. Rayleigh fading channel show that the total transmit power can be reduced linearly with increasing $N$ (i.e., an O(N) array gain). We also propose a precoding scheme which finds near-optimal CE signals to be transmitted, and has O(MN) complexity. Also, in terms of the total transmit power required to achieve a fixed desired information sum-rate, despite the stringent per-antenna CE constraint, the proposed CE precoding scheme performs close to the sum-capacity achieving scheme for an average-only total transmit power constrained channel.

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Single-User Beamforming in Large-Scale MISO Systems with Per-Antenna Constant-Envelope Constraints: The Doughnut Channel

Large antenna arrays at the base station (BS) has recently been shown to achieve remarkable intra-cell interference suppression at low complexity. However, building large arrays in practice, would require the use of power-efficient RF amplifiers, which generally have poor linearity characteristics and hence would require the use of input signals with a very small peak-to-average power ratio (PAPR). In this paper, we consider the single-user Multiple-Input Single-Output (MISO) downlink channel for the case where the BS antennas are constrained to transmit signals having constant envelope (CE). We show that, with per-antenna CE transmission the effective channel seen by the receiver is a SISO AWGN channel with its input constrained to lie in a doughnut-shaped region. For single-path direct-line-of-sight (DLOS) and general i.i.d. fading channels, analysis of the effective doughnut channel shows that under a per-antenna CE input constraint, i) compared to an average-only total transmit power constrained MISO channel, the extra total transmit power required to achieve a desired information rate is small and bounded, ii) with N base station antennas an O(N) array power gain is achievable, and iii) for a desired information rate, using power-efficient amplifiers with CE inputs would require significantly less total transmit power when compared to using highly linear (power-inefficient) amplifiers with high PAPR inputs.

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Constant Envelope Precoding for Power-Efficient Downlink Wireless Communication in Multi-User MIMO Systems Using Large Antenna Arrays

We consider downlink cellular multi-user communication between a base station (BS) having N antennas and M single-antenna users, i.e., an N X M Gaussian Broadcast Channel (GBC). Under an average only total transmit power constraint (APC), large antenna arrays at the BS (having tens to a few hundred antennas) have been recently shown to achieve remarkable multi-user interference (MUI) suppression with simple precoding techniques. However, building large arrays in practice, would require cheap/power-efficient Radio-Frequency(RF) electronic components. The type of transmitted signal that facilitates the use of most power-efficient RF components is a constant envelope (CE) signal. Under certain mild channel conditions (including i.i.d. fading), we analytically show that, even under the stringent per-antenna CE transmission constraint (compared to APC), MUI suppression can still be achieved with large antenna arrays. Our analysis also reveals that, with a fixed M and increasing N, the total transmitted power can be reduced while maintaining a constant signal-to-interference-noise-ratio (SINR) level at each user. We also propose a novel low-complexity CE precoding scheme, using which, we confirm our analytical observations for the i.i.d. Rayleigh fading channel, through Monte-Carlo simulations. Simulation of the information sum-rate under the per-antenna CE constraint, shows that, for a fixed M and a fixed desired sum-rate, the required total transmit power decreases linearly with increasing N, i.e., an O(N) array power gain. Also, in terms of the total transmit power required to achieve a fixed desired information sum-rate, despite the stringent per-antenna CE constraint, the proposed CE precoding scheme performs close to the GBC sum-capacity (under APC) achieving scheme.

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Modulation Diversity in Fading Channels with Quantized Receiver

In this paper, we address the design of codes which achieve modulation diversity in block fading single-input single-output (SISO) channels with signal quantization at receiver and low-complexity decoding. With an unquantized receiver, coding based on algebraic rotations is known to achieve modulation coding diversity. On the other hand, with a quantized receiver, algebraic rotations may not guarantee diversity. Through analysis, we propose specific rotations which result in the codewords having equidistant component-wise projections. We show that the proposed coding scheme achieves maximum modulation diversity with a low-complexity minimum distance decoder and perfect channel knowledge. Relaxing the perfect channel knowledge assumption we propose a novel training/estimation and receiver control technique to estimate the channel. We show that our coding/training/estimation scheme and minimum distance decoding achieve an error probability performance similar to that achieved with perfect channel knowledge.

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Precoding by Pairing Subchannels to Increase MIMO Capacity with Discrete Input Alphabets

We consider Gaussian multiple-input multiple-output (MIMO) channels with discrete input alphabets. We propose a non-diagonal precoder based on the X-Codes in \cite{Xcodes_paper} to increase the mutual information. The MIMO channel is transformed into a set of parallel subchannels using Singular Value Decomposition (SVD) and X-Codes are then used to pair the subchannels. X-Codes are fully characterized by the pairings and a $2\times 2$ real rotation matrix for each pair (parameterized with a single angle). This precoding structure enables us to express the total mutual information as a sum of the mutual information of all the pairs. The problem of finding the optimal precoder with the above structure, which maximizes the total mutual information, is solved by {\em i}) optimizing the rotation angle and the power allocation within each pair and {\em ii}) finding the optimal pairing and power allocation among the pairs. It is shown that the mutual information achieved with the proposed pairing scheme is very close to that achieved with the optimal precoder by Cruz {\em et al.}, and is significantly better than Mercury/waterfilling strategy by Lozano {\em et al.}. Our approach greatly simplifies both the precoder optimization and the detection complexity, making it suitable for practical applications.

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MIMO Precoding with X- and Y-Codes

We consider a time division duplex (TDD) $n_t \times n_r$ multiple-input multiple-output (MIMO) system with channel state information (CSI) at both the transmitter and receiver. We propose X- and Y-Codes to achieve high multiplexing and diversity gains at low complexity. The proposed precoding schemes are based upon the singular value decomposition (SVD) of the channel matrix which transforms the MIMO channel into parallel subchannels. Then X- and Y-Codes are used to improve the diversity gain by pairing the subchannels, prior to SVD precoding. In particular, the subchannels with good diversity are paired with those having low diversity gains. Hence, a pair of channels is jointly encoded using a $2 \times 2$ real matrix, which is fixed {\em a priori} and does not change with each channel realization. For X-Codes these matrices are 2-dimensional rotation matrices parameterized by a single angle, while for Y-Codes, these matrices are 2-dimensional upper left triangular matrices. The complexity of the maximum likelihood decoding (MLD) for both X- and Y-Codes is low. Specifically, the decoding complexity of Y-Codes is the same as that of a scalar channel. Moreover, we propose X-, Y-Precoders with the same structure as X-, Y-Codes, but the encoding matrices adapt to each channel realization. The optimal encoding matrices for X-, Y-Codes/Precoders are derived analytically. Finally, it is observed that X-Codes/Precoders perform better for well-conditioned channels, while Y-Codes/Precoders perform better for ill-conditioned channels, when compared to other precoding schemes in the literature.

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