1,645 research outputs found
Asymptotic Performance of Linear Receivers in MIMO Fading Channels
Linear receivers are an attractive low-complexity alternative to optimal
processing for multi-antenna MIMO communications. In this paper we characterize
the information-theoretic performance of MIMO linear receivers in two different
asymptotic regimes. For fixed number of antennas, we investigate the limit of
error probability in the high-SNR regime in terms of the Diversity-Multiplexing
Tradeoff (DMT). Following this, we characterize the error probability for fixed
SNR in the regime of large (but finite) number of antennas.
As far as the DMT is concerned, we report a negative result: we show that
both linear Zero-Forcing (ZF) and linear Minimum Mean-Square Error (MMSE)
receivers achieve the same DMT, which is largely suboptimal even in the case
where outer coding and decoding is performed across the antennas. We also
provide an approximate quantitative analysis of the markedly different behavior
of the MMSE and ZF receivers at finite rate and non-asymptotic SNR, and show
that while the ZF receiver achieves poor diversity at any finite rate, the MMSE
receiver error curve slope flattens out progressively, as the coding rate
increases.
When SNR is fixed and the number of antennas becomes large, we show that the
mutual information at the output of a MMSE or ZF linear receiver has
fluctuations that converge in distribution to a Gaussian random variable, whose
mean and variance can be characterized in closed form. This analysis extends to
the linear receiver case a well-known result previously obtained for the
optimal receiver. Simulations reveal that the asymptotic analysis captures
accurately the outage behavior of systems even with a moderate number of
antennas.Comment: 48 pages, Submitted to IEEE Transactions on Information Theor
Spectral Efficiency of One-Bit Sigma-Delta Massive MIMO
We examine the uplink spectral efficiency of a massive MIMO base station employing a one-bit Sigma-Delta ( \Sigma \Delta ) sampling scheme implemented in the spatial rather than the temporal domain. Using spatial rather than temporal oversampling, and feedback of the quantization error between adjacent antennas, the method shapes the spatial spectrum of the quantization noise away from an angular sector where the signals of interest are assumed to lie. It is shown that, while a direct Bussgang analysis of the \Sigma \Delta approach is not suitable, an alternative equivalent linear model can be formulated to facilitate an analysis of the system performance. The theoretical properties of the spatial quantization noise power spectrum are derived for the \Sigma \Delta array, as well as an expression for the spectral efficiency of maximum ratio combining (MRC). Simulations verify the theoretical results and illustrate the significant performance gains offered by the \Sigma \Delta approach for both MRC and zero-forcing receivers
Power Control for D2D Underlay in Multi-cell Massive MIMO Networks
This paper proposes a new power control and pilot allocation scheme for
device-to-device (D2D) communication underlaying a multi-cell massive MIMO
system. In this scheme, the cellular users in each cell get orthogonal pilots
which are reused with reuse factor one across cells, while the D2D pairs share
another set of orthogonal pilots. We derive a closed-form capacity lower bound
for the cellular users with different receive processing schemes. In addition,
we derive a capacity lower bound for the D2D receivers and a closed-form
approximation of it. Then we provide a power control algorithm that maximizes
the minimum spectral efficiency (SE) of the users in the network. Finally, we
provide a numerical evaluation where we compare our proposed power control
algorithm with the maximum transmit power case and the case of conventional
multi-cell massive MIMO without D2D communication. Based on the provided
results, we conclude that our proposed scheme increases the sum spectral
efficiency of multi-cell massive MIMO networks.Comment: 6 Pages, 3 Figures, WSA 201
Spectral Efficiency of Mixed-ADC Massive MIMO
We study the spectral efficiency (SE) of a mixed-ADC massive MIMO system in
which K single-antenna users communicate with a base station (BS) equipped with
M antennas connected to N high-resolution ADCs and M-N one-bit ADCs. This
architecture has been proposed as an approach for realizing massive MIMO
systems with reasonable power consumption. First, we investigate the
effectiveness of mixed-ADC architectures in overcoming the channel estimation
error caused by coarse quantization. For the channel estimation phase, we study
to what extent one can combat the SE loss by exploiting just N << M pairs of
high-resolution ADCs. We extend the round-robin training scheme for mixed-ADC
systems to include both high-resolution and one-bit quantized observations.
Then, we analyze the impact of the resulting channel estimation error in the
data detection phase. We consider random high-resolution ADC assignment and
also analyze a simple antenna selection scheme to increase the SE. Analytical
expressions are derived for the SE for maximum ratio combining (MRC) and
numerical results are presented for zero-forcing (ZF) detection. Performance
comparisons are made against systems with uniform ADC resolution and against
mixed-ADC systems without round-robin training to illustrate under what
conditions each approach provides the greatest benefit.Comment: To appear in IEEE Transactions on Signal Processin
- …