5 research outputs found
Performance Analysis of Channel Extrapolation in FDD Massive MIMO Systems
Channel estimation for the downlink of frequency division duplex (FDD)
massive MIMO systems is well known to generate a large overhead as the amount
of training generally scales with the number of transmit antennas in a MIMO
system. In this paper, we consider the solution of extrapolating the channel
frequency response from uplink pilot estimates to the downlink frequency band,
which completely removes the training overhead. We first show that conventional
estimators fail to achieve reasonable accuracy. We propose instead to use
high-resolution channel estimation. We derive theoretical lower bounds (LB) for
the mean squared error (MSE) of the extrapolated channel. Assuming that the
paths are well separated, the LB is simplified in an expression that gives
considerable physical insight. It is then shown that the MSE is inversely
proportional to the number of receive antennas while the extrapolation
performance penalty scales with the square of the ratio of the frequency offset
and the training bandwidth. The channel extrapolation performance is validated
through numeric simulations and experimental measurements taken in an anechoic
chamber. Our main conclusion is that channel extrapolation is a viable solution
for FDD massive MIMO systems if accurate system calibration is performed and
favorable propagation conditions are present.Comment: arXiv admin note: substantial text overlap with arXiv:1902.0684
6G Wireless Systems: Vision, Requirements, Challenges, Insights, and Opportunities
Mobile communications have been undergoing a generational change every ten
years or so. However, the time difference between the so-called "G's" is also
decreasing. While fifth-generation (5G) systems are becoming a commercial
reality, there is already significant interest in systems beyond 5G, which we
refer to as the sixth-generation (6G) of wireless systems. In contrast to the
already published papers on the topic, we take a top-down approach to 6G. We
present a holistic discussion of 6G systems beginning with lifestyle and
societal changes driving the need for next generation networks. This is
followed by a discussion into the technical requirements needed to enable 6G
applications, based on which we dissect key challenges, as well as
possibilities for practically realizable system solutions across all layers of
the Open Systems Interconnection stack. Since many of the 6G applications will
need access to an order-of-magnitude more spectrum, utilization of frequencies
between 100 GHz and 1 THz becomes of paramount importance. As such, the 6G
eco-system will feature a diverse range of frequency bands, ranging from below
6 GHz up to 1 THz. We comprehensively characterize the limitations that must be
overcome to realize working systems in these bands; and provide a unique
perspective on the physical, as well as higher layer challenges relating to the
design of next generation core networks, new modulation and coding methods,
novel multiple access techniques, antenna arrays, wave propagation,
radio-frequency transceiver design, as well as real-time signal processing. We
rigorously discuss the fundamental changes required in the core networks of the
future that serves as a major source of latency for time-sensitive
applications. While evaluating the strengths and weaknesses of key 6G
technologies, we differentiate what may be achievable over the next decade,
relative to what is possible.Comment: Accepted for Publication into the Proceedings of the IEEE; 32 pages,
10 figures, 5 table
Performance Analysis of Channel Extrapolation in FDD Massive MIMO Systems
Channel estimation for the downlink of frequency division duplex (FDD) massive MIMO systems is well known to generate a large overhead as the amount of training generally scales with the number of transmit antennas in a MIMO system. In this paper, we consider the solution of extrapolating the channel frequency response from uplink pilot estimates to the downlink frequency band. This drastically reduces the downlink pilot overhead and completely removes the need for a feedback from the users. The price to pay is a degradation in the quality of the channel estimates, which reduces the downlink spectral efficiency. We first show that conventional estimators fail to achieve reasonable accuracy. We propose instead to use high-resolution channel estimation. We derive the Cramer-Rao lower bound (CRLB) of the mean squared error (MSE) of the extrapolated channel. Furthermore, a relationship between the imperfect channel state information (CSI) and the downlink user performance is derived. The extrapolation-based FDD massive MIMO performance is validated through numerical simulations and compared to a corresponding time division duplex (TDD) system. Considered figures of merit for extrapolation performance include channel MSE, beamforming efficiency, extrapolation range, spectral efficiency and uncoded symbol error rate. Our main conclusion is that channel extrapolation is a viable solution for FDD massive MIMO systems