56 research outputs found
Receive Combining vs. Multi-Stream Multiplexing in Downlink Systems with Multi-Antenna Users
In downlink multi-antenna systems with many users, the multiplexing gain is
strictly limited by the number of transmit antennas and the use of these
antennas. Assuming that the total number of receive antennas at the
multi-antenna users is much larger than , the maximal multiplexing gain can
be achieved with many different transmission/reception strategies. For example,
the excess number of receive antennas can be utilized to schedule users with
effective channels that are near-orthogonal, for multi-stream multiplexing to
users with well-conditioned channels, and/or to enable interference-aware
receive combining. In this paper, we try to answer the question if the data
streams should be divided among few users (many streams per user) or many users
(few streams per user, enabling receive combining). Analytic results are
derived to show how user selection, spatial correlation, heterogeneous user
conditions, and imperfect channel acquisition (quantization or estimation
errors) affect the performance when sending the maximal number of streams or
one stream per scheduled user---the two extremes in data stream allocation.
While contradicting observations on this topic have been reported in prior
works, we show that selecting many users and allocating one stream per user
(i.e., exploiting receive combining) is the best candidate under realistic
conditions. This is explained by the provably stronger resilience towards
spatial correlation and the larger benefit from multi-user diversity. This
fundamental result has positive implications for the design of downlink systems
as it reduces the hardware requirements at the user devices and simplifies the
throughput optimization.Comment: Published in IEEE Transactions on Signal Processing, 16 pages, 11
figures. The results can be reproduced using the following Matlab code:
https://github.com/emilbjornson/one-or-multiple-stream
Dexterity for Channel Capacity Enhancement in MU-MIMO by Abrogating Interference
The looming field of Multi user Multiple-input Multiple-output (MU-MIMO) communication system has faced a challenge with precoding techniques for achieving increased channel capacity of their less inhaling of signals, imperfect knowing of channel state information, loss of signals by noise ,time complexity etc. in downlink systems which results in interference to the users. Hence straight forwarding from the issues, the paper newly introduce2LB-FR precoding technique which holds Linde-Lyold’s (LL)algorithm to increase data transmission by consuming large amount of signals with space and the Bernoulli distribution with Bayes decision (BB) to allot the perfect channel state; l information during transmission that eliminates co-interference. Holding Floyd Rasta (FR) algorithm expels the noise if added and takes the shortest required path by acquiring all the possible routes available in single execution which decreases delay. By the overall implementation, the proposed work pomped that in short time ,the capacity of the channel get enhanced with interference cancellation
Interleaving Channel Estimation and Limited Feedback for Point-to-Point Systems with a Large Number of Transmit Antennas
We introduce and investigate the opportunities of multi-antenna communication
schemes whose training and feedback stages are interleaved and mutually
interacting. Specifically, unlike the traditional schemes where the transmitter
first trains all of its antennas at once and then receives a single feedback
message, we consider a scenario where the transmitter instead trains its
antennas one by one and receives feedback information immediately after
training each one of its antennas. The feedback message may ask the transmitter
to train another antenna; or, it may terminate the feedback/training phase and
provide the quantized codeword (e.g., a beamforming vector) to be utilized for
data transmission. As a specific application, we consider a multiple-input
single-output system with transmit antennas, a short-term power constraint
, and target data rate . We show that for any , the same outage
probability as a system with perfect transmitter and receiver channel state
information can be achieved with a feedback rate of bits per channel
state and via training transmit antennas on average, where and
are independent of , and depend only on and . In addition,
we design variable-rate quantizers for channel coefficients to further minimize
the feedback rate of our scheme.Comment: To appear in IEEE Transactions on Wireless Communication
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