118 research outputs found
Full-Duplex Massive MIMO Relaying Systems with Low-Resolution ADCs
International audienceThis paper considers a multipair amplify-and-forward massive MIMO relaying system with low-resolution analog-to-digital converters (ADCs) at both the relay and destinations. The channel state information (CSI) at the relay is obtained via pilot training, which is then utilized to perform simple maximum-ratio combining/maximum-ratio transmission processing by the relay. Also, it is assumed that the destinations use statistical CSI to decode the transmitted signals. Exact and approximated closed-form expressions for the achievable sum rate are presented, which enable the efficient evaluation of the impact of key system parameters on the system performance. In addition, optimal relay power allocation scheme is studied, and power scaling law is characterized. It is found that, with only low-resolution ADCs at the relay, increasing the number of relay antennas is an effective method to compensate for the rate loss caused by coarse quantization. However, it becomes ineffective to handle the detrimental effect of low-resolution ADCs at the destination. Moreover, it is shown that deploying massive relay antenna arrays can still bring significant power savings, i.e., the transmit power of each source can be cut down proportional to 1/M to maintain a constant rate, where M is the number of relay antennas
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
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
Hardware Impairments Aware Transceiver Design for Full-Duplex Amplify-and-Forward MIMO Relaying
In this work we study the behavior of a full-duplex (FD) and
amplify-and-forward (AF) relay with multiple antennas, where hardware
impairments of the FD relay transceiver is taken into account. Due to the
inter-dependency of the transmit relay power on each antenna and the residual
self-interference in an FD-AF relay, we observe a distortion loop that degrades
the system performance when the relay dynamic range is not high. In this
regard, we analyze the relay function in presence of the hardware inaccuracies
and an optimization problem is formulated to maximize the signal to
distortion-plus-noise ratio (SDNR), under relay and source transmit power
constraints. Due to the problem complexity, we propose a
gradient-projection-based (GP) algorithm to obtain an optimal solution.
Moreover, a nonalternating sub-optimal solution is proposed by assuming a
rank-1 relay amplification matrix, and separating the design of the relay
process into multiple stages (MuStR1). The proposed MuStR1 method is then
enhanced by introducing an alternating update over the optimization variables,
denoted as AltMuStR1 algorithm. It is observed that compared to GP, (Alt)MuStR1
algorithms significantly reduce the required computational complexity at the
expense of a slight performance degradation. Finally, the proposed methods are
evaluated under various system conditions, and compared with the methods
available in the current literature. In particular, it is observed that as the
hardware impairments increase, or for a system with a high transmit power, the
impact of applying a distortion-aware design is significant.Comment: Submitted to IEEE Transactions on Wireless Communication
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