144 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
Optimize Power Allocation Scheme to Maximize Sum Rate in CoMP with Limited Channel State Information
Extensive use of mobile applications throws many challenges in cellular systems like cell edge
throughput, inter cell interference and spectral e�ciency. Many of these challenges have been
resolved using Coordinated Multi-Point (CoMP), developed in the Third Generation Partnership
Project for LTE-Advanced) to a great extent. CoMP cooperatively process signals from base sta-
tions that are connected to various multiple terminals (user equipment (UEs)) at transmission and
reception. This CoMP improves throughput, reduces or even removes inter-cell interference and
increases spectral e�ciency in the downlink of multi-antenna coordinated multipoint systems.
Many researchers addressed these issues assuming that BSs have the knowledge of the common
control channels dedicated to all UEs and also about the full or partial channel state information
(CSI) of all the links. From the CSI available at the BSs, multiuser interference can be managed
at the BSs. To make this feasible, UEs are responsible for collecting downlink CSI. But, CSI
measurement (instantaneous and/or statistical) is imperfect in nature because of the randomly
varying nature of the channels at random times. These incorrect CSI values available at the BSs
may, in turn, create multi-user interference. There are many techniques to suppress the multi-user
interference, among which the feedback scheme is the one which is gaining a lot of attention. In
feedback schemes, CSI information needs to be fed back to the base station from UEs in the uplink.
It is obvious, the question arises on the type and amount of feedback need to be used. Research
has been progressing in this front and some feedback techniques have been proposed. Three basic
CoMP Feedback schemes are available. Explicit or statistical channel information feedback scheme
in which channel information like channels's covariance matrix of the channel are shared between the
transmitter and receiver. Next, implicit or statistical channel information feedback which contains
information such as Channel quality indication or Precoding matrix indicator or Rank indicator. 1st
applied to TDD LTE type structure and 2nd of feedback scheme can be applied in the FDD system.
Finally, we have UE which tranmit the sounding reference signal (CSI). This type of feedback scheme
is applied to exploit channel reciprocity and to reduce channel intercell interference and this can be
applied in the TDD system. We have analyzed the scenario of LTE TDD based system. After this,
optimization of power is also required because users at the cell edge required more attention than
the user locating at the center of the cell. In my work, it shows estimated power gives exponential
divercity for high SNR as low SNR too.
In this method, a compression feedback method is analyzed to provide multi-cell spatial channel
information. It improves the feedback e�ciency and throughput. The rows and columns of the
channel matrix are compressed using Eigenmode of the user and codebook based scheme speci�ed
in LTE speci�cation. The main drawback of this scheme is that spectral e�ciency is achieved with
the cost of increased overheads for feedback and evolved NodeB (eNB). Other factor is complexity
of eNodeB which is to be addressed in future work
Channel estimation in massive MIMO systems
Last years were characterized by a great demand for high data throughput, good quality and spectral efficiency in wireless communication systems. Consequently, a revolution in cellular networks has been set in motion towards to 5G. Massive multiple-input multiple-output (MIMO) is one of the new concepts in 5G and the idea is to scale up the known MIMO systems in unprecedented proportions, by deploying hundreds of antennas at base stations. Although, perfect channel knowledge is crucial in these systems for user and data stream separation in order to cancel interference.
The most common way to estimate the channel is based on pilots. However, problems such as interference and pilot contamination (PC) can arise due to the multiplicity of channels in the wireless link. Therefore, it is crucial to define techniques for channel estimation that together with pilot contamination mitigation allow best system performance and at same time low complexity.
This work introduces a low-complexity channel estimation technique based on Zadoff-Chu training sequences. In addition, different approaches were studied towards pilot contamination mitigation and low complexity schemes, with resort to iterative channel estimation methods, semi-blind subspace tracking techniques and matrix inversion substitutes.
System performance simulations were performed for the several proposed techniques in order to identify the best tradeoff between complexity, spectral efficiency and system performance
Multiuser Precoding and Channel Estimation for Hybrid Millimeter Wave MIMO Systems
In this paper, we develop a low-complexity channel estimation for hybrid
millimeter wave (mmWave) systems, where the number of radio frequency (RF)
chains is much less than the number of antennas equipped at each transceiver.
The proposed channel estimation algorithm aims to estimate the strongest
angle-of-arrivals (AoAs) at both the base station (BS) and the users. Then all
the users transmit orthogonal pilot symbols to the BS via these estimated
strongest AoAs to facilitate the channel estimation. The algorithm does not
require any explicit channel state information (CSI) feedback from the users
and the associated signalling overhead of the algorithm is only proportional to
the number of users, which is significantly less compared to various existing
schemes. Besides, the proposed algorithm is applicable to both non-sparse and
sparse mmWave channel environments. Based on the estimated CSI, zero-forcing
(ZF) precoding is adopted for multiuser downlink transmission. In addition, we
derive a tight achievable rate upper bound of the system. Our analytical and
simulation results show that the proposed scheme offer a considerable
achievable rate gain compared to fully digital systems, where the number of RF
chains equipped at each transceiver is equal to the number of antennas.
Furthermore, the achievable rate performance gap between the considered hybrid
mmWave systems and the fully digital system is characterized, which provides
useful system design insights.Comment: 6 pages, accepted for presentation, ICC 201
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