32 research outputs found
Hybrid Processing Design for Multipair Massive MIMO Relaying with Channel Spatial Correlation
Massive multiple-input multiple-output (MIMO) avails of simple transceiver
design which can tackle many drawbacks of relay systems in terms of complicated
signal processing, latency, and noise amplification. However, the cost and
circuit complexity of having one radio frequency (RF) chain dedicated to each
antenna element are prohibitive in practice. In this paper, we address this
critical issue in amplify-and-forward (AF) relay systems using a hybrid analog
and digital (A/D) transceiver structure. More specifically, leveraging the
channel long-term properties, we design the analog beamformer which aims to
minimize the channel estimation error and remain invariant over a long
timescale. Then, the beamforming is completed by simple digital signal
processing, i.e., maximum ratio combining/maximum ratio transmission (MRC/MRT)
or zero-forcing (ZF) in the baseband domain. We present analytical bounds on
the achievable spectral efficiency taking into account the spatial correlation
and imperfect channel state information at the relay station. Our analytical
results reveal that the hybrid A/D structure with ZF digital processor exploits
spatial correlation and offers a higher spectral efficiency compared to the
hybrid A/D structure with MRC/MRT scheme. Our numerical results showcase that
the hybrid A/D beamforming design captures nearly 95% of the spectral
efficiency of a fully digital AF relaying topology even by removing half of the
RF chains. It is also shown that the hybrid A/D structure is robust to coarse
quantization, and even with 2-bit resolution, the system can achieve more than
93% of the spectral efficiency offered by the same hybrid A/D topology with
infinite resolution phase shifters.Comment: 17 pages, 13 figures, to appear in IEEE Transactions on
Communication
Multipair Massive MIMO Relaying Systems with One-Bit ADCs and DACs
This paper considers a multipair amplify-and-forward massive MIMO relaying
system with one-bit ADCs and one-bit DACs at the relay. The channel state
information is estimated via pilot training, and then utilized by the relay to
perform simple maximum-ratio combining/maximum-ratio transmission processing.
Leveraging on the Bussgang decomposition, an exact achievable rate is derived
for the system with correlated quantization noise. Based on this, a closed-form
asymptotic approximation for the achievable rate is presented, thereby enabling
efficient evaluation of the impact of key parameters on the system performance.
Furthermore, power scaling laws are characterized to study the potential energy
efficiency associated with deploying massive one-bit antenna arrays at the
relay. In addition, a power allocation strategy is designed to compensate for
the rate degradation caused by the coarse quantization. Our results suggest
that the quality of the channel estimates depends on the specific orthogonal
pilot sequences that are used, contrary to unquantized systems where any set of
orthogonal pilot sequences gives the same result. Moreover, the sum rate gap
between the double-quantized relay system and an ideal non-quantized system is
a moderate factor of in the low power regime.Comment: 14 pages, 10 figures, submitted to IEEE Trans. Signal Processin
Multipair Relaying With Space-Constrained Large-Scale MIMO Arrays: Spectral and Energy Efficiency Analysis With Incomplete CSI
In this paper, we study a multi-pair two-way large-scale multiple-input multiple-output (MIMO) decode-and-forward relay system. Multiple single-antenna user pairs exchange information via a shared relay working at half-duplex. The proposed scenario considers a practical case where an increasing number of antennas is deployed in a fixed physical space, giving rise to a trade-off between antenna gain and spatial correlation. The channel is assumed imperfectly known, and the relay employs linear processing methods. We study the large-scale approximations of the sum spectral efficiency (SE) and investigate the energy efficiency (EE) with a practical power consumption model when the number of relay antennas becomes large. We demonstrate the impact of the relay antenna number and spatial correlation with reducing inter-antenna distance on the EE performance. We exploit the increasing spatial correlation to allow an incomplete channel state information (CSI) acquisition where explicit CSI is acquired only for a subset of antennas. Our analytical derivations and numerical results show that applying the incomplete CSI strategy in the proposed system can improve the EE against complete CSI systems while maintaining the average SE performance
Massive MIMO and Full-duplex Relaying Systems
In this thesis, we study how massive multiple-input and multiple-output (MIMO) can be employed to mitigate loop-interference (LI), multi-user interference and noise in a full-duplex (FD) relaying system. For a FD relaying system with massive MIMO deployed at both source and destination, we investigate three FD relaying schemes: co-located, distributed cooperative, and distributed non-cooperative relaying. Asymptotic analysis shows that the three schemes can completely cancel multi-user interference and LI when the number of antennas at the source and destination grows without bound, in the case where the relay has a finite number of antennas. For the system with massive MIMO deployed at the FD relay, we propose a pilot protocol for LI channel minimum-mean-square-error estimation by exploiting the channel coherence time difference between static and moving transceivers. To maximize the end-to-end achievable rate, we design a novel power allocation scheme to adjust the transmit power of each link at the relay in order to equalize the achievable rate of the source-to-relay and relay-to-destination links. The analytical and numerical results show that the proposed pilot protocol and power allocation scheme jointly improve both spectral and energy efficiency significantly. To enable the use of low resolution analog-to-digital converters (ADCs) at relays for energy saving, we propose a novel iterative power allocation scheme to mitigate the resulting quantization noise via reducing the received LI power and numerically identify the optimum resolutions of ADCs for maximizing throughput and energy efficiency. For massive MIMO receivers employing one-bit ADCs, we propose three carrier frequency (CFO) offset estimation schemes for dual-pilot and multiple-pilot cases. The three schemes are developed under different scenarios: large but finite number of antennas at the receiver, infinite number of antennas at the receiver, and very small CFO, respectively
Energy Efficient Massive MIMO and Beamforming for 5G Communications
Massive multiple-input multiple-output (MIMO) has been a key technique
in the next generation of wireless communications for its potential to achieve
higher capacity and data rates. However, the exponential growth of data
traffic has led to a significant increase in the power consumption and system
complexity. Therefore, we propose and study wireless technologies to improve the trade-off between system performance and power consumption of wireless communications.
This Thesis firstly proposes a strategy with partial channel state information
(CSI) acquisition to reduce the power consumption and hardware complexity of massive MIMO base stations. In this context, the employment of partial CSI is proposed in correlated communication channels with user mobility. By exploiting both the spatial correlation and temporal correlation of the channel, our analytical results demonstrate significant gains in the energy efficiency of the massive MIMO base station.
Moreover, relay-aided communications have experienced raising interest; especially, two-way relaying systems can improve spectral efficiency with short required operating time. Therefore, this Thesis focuses on an uncorrelated massive MIMO two-way relaying system and studies power
scaling laws to investigate how the transmit powers can be scaled to improve the energy efficiency up to several times the energy efficiency without power scaling while approximately maintaining the system performance.
In a similar line, large antenna arrays deployed at the space-constrained relay would give rise to the spatial correlation. For this reason, this Thesis presents an incomplete CSI scheme to evaluate the trade-off between the spatial correlation and system performance. In addition, the advantages of linear processing methods and the effects of channel aging are investigated to further improve the relay-aided system performance.
Similarly, large antenna arrays are required in millimeter-wave communications to achieve narrow beams with higher power gain. This poses the problem that locating the best beam direction requires high power and complexity consumption. Therefore, this Thesis presents several low-complexity beam alignment methods with respect to the state-of-the-art to evaluate the trade-off between complexity and system performance.
Overall, extensive analytical and numerical results show an improved performance and validate the effectiveness of the proposed techniques
Advanced Tri-Sectoral Multi-User Millimeter-Wave Smart Repeater
Smart Repeaters (SR) can potentially enhance the coverage in Millimeter-wave
(mmWave) wireless communications. However, the angular coverage of the existing
two-panel SR is too limited to make the SR a truly cost-effective mmWave range
extender. This paper proposes the usage of a tri-sectoral Advanced SR (ASR) to
extend the angular coverage with respect to conventional SR. We propose a
multi-user precoder optimization for ASR in a downlink multi-carrier
communication system to maximize the number of served User Equipments (UEs)
while guaranteeing constraints on per-UE rate and time-frequency resources.
Numerical results show the benefits of the ASR against conventional SR in terms
of both cumulative spectral efficiency and number of served UEs (both improved
by an average factor 2), varying the system parameters