2,650 research outputs found
MIMO Transmission with Residual Transmit-RF Impairments
Physical transceiver implementations for multiple-input multiple-output
(MIMO) wireless communication systems suffer from transmit-RF (Tx-RF)
impairments. In this paper, we study the effect on channel capacity and
error-rate performance of residual Tx-RF impairments that defy proper
compensation. In particular, we demonstrate that such residual distortions
severely degrade the performance of (near-)optimum MIMO detection algorithms.
To mitigate this performance loss, we propose an efficient algorithm, which is
based on an i.i.d. Gaussian model for the distortion caused by these
impairments. In order to validate this model, we provide measurement results
based on a 4-stream Tx-RF chain implementation for MIMO orthogonal
frequency-division multiplexing (OFDM).Comment: to be presented at the International ITG Workshop on Smart Antennas -
WSA 201
Advanced Radio Resource Management for Multi Antenna Packet Radio Systems
In this paper, we propose fairness-oriented packet scheduling (PS) schemes
with power-efficient control mechanism for future packet radio systems. In
general, the radio resource management functionality plays an important role in
new OFDMA based networks. The control of the network resource division among
the users is performed by packet scheduling functionality based on maximizing
cell coverage and capacity satisfying, and certain quality of service
requirements. Moreover, multiantenna transmit-receive schemes provide
additional flexibility to packet scheduler functionality. In order to mitigate
inter-cell and co-channel interference problems in OFDMA cellular networks soft
frequency reuse with different power masks patterns is used. Stemming from the
earlier enhanced proportional fair scheduler studies for single-input
multiple-output (SIMO) and multiple-input multipleoutput (MIMO) systems, we
extend the development of efficient packet scheduling algorithms by adding
transmit power considerations in the overall priority metrics calculations and
scheduling decisions. Furthermore, we evaluate the proposed scheduling schemes
by simulating practical orthogonal frequency division multiple access (OFDMA)
based packet radio system in terms of throughput, coverage and fairness
distribution among users. As a concrete example, under reduced overall transmit
power constraint and unequal power distribution for different sub-bands, we
demonstrate that by using the proposed power-aware multi-user scheduling
schemes, significant coverage and fairness improvements in the order of 70% and
20%, respectively, can be obtained, at the expense of average throughput loss
of only 15%.Comment: 14 Pages, IJWM
Efficient DSP and Circuit Architectures for Massive MIMO: State-of-the-Art and Future Directions
Massive MIMO is a compelling wireless access concept that relies on the use
of an excess number of base-station antennas, relative to the number of active
terminals. This technology is a main component of 5G New Radio (NR) and
addresses all important requirements of future wireless standards: a great
capacity increase, the support of many simultaneous users, and improvement in
energy efficiency. Massive MIMO requires the simultaneous processing of signals
from many antenna chains, and computational operations on large matrices. The
complexity of the digital processing has been viewed as a fundamental obstacle
to the feasibility of Massive MIMO in the past. Recent advances on
system-algorithm-hardware co-design have led to extremely energy-efficient
implementations. These exploit opportunities in deeply-scaled silicon
technologies and perform partly distributed processing to cope with the
bottlenecks encountered in the interconnection of many signals. For example,
prototype ASIC implementations have demonstrated zero-forcing precoding in real
time at a 55 mW power consumption (20 MHz bandwidth, 128 antennas, multiplexing
of 8 terminals). Coarse and even error-prone digital processing in the antenna
paths permits a reduction of consumption with a factor of 2 to 5. This article
summarizes the fundamental technical contributions to efficient digital signal
processing for Massive MIMO. The opportunities and constraints on operating on
low-complexity RF and analog hardware chains are clarified. It illustrates how
terminals can benefit from improved energy efficiency. The status of technology
and real-life prototypes discussed. Open challenges and directions for future
research are suggested.Comment: submitted to IEEE transactions on signal processin
Soft-Decision-Driven Channel Estimation for Pipelined Turbo Receivers
We consider channel estimation specific to turbo equalization for
multiple-input multiple-output (MIMO) wireless communication. We develop a
soft-decision-driven sequential algorithm geared to the pipelined turbo
equalizer architecture operating on orthogonal frequency division multiplexing
(OFDM) symbols. One interesting feature of the pipelined turbo equalizer is
that multiple soft-decisions become available at various processing stages. A
tricky issue is that these multiple decisions from different pipeline stages
have varying levels of reliability. This paper establishes an effective
strategy for the channel estimator to track the target channel, while dealing
with observation sets with different qualities. The resulting algorithm is
basically a linear sequential estimation algorithm and, as such, is
Kalman-based in nature. The main difference here, however, is that the proposed
algorithm employs puncturing on observation samples to effectively deal with
the inherent correlation among the multiple demapper/decoder module outputs
that cannot easily be removed by the traditional innovations approach. The
proposed algorithm continuously monitors the quality of the feedback decisions
and incorporates it in the channel estimation process. The proposed channel
estimation scheme shows clear performance advantages relative to existing
channel estimation techniques.Comment: 11 pages; IEEE Transactions on Communications 201
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