1,771 research outputs found
Fundamental Limits of Cooperation
Cooperation is viewed as a key ingredient for interference management in
wireless systems. This paper shows that cooperation has fundamental
limitations. The main result is that even full cooperation between transmitters
cannot in general change an interference-limited network to a noise-limited
network. The key idea is that there exists a spectral efficiency upper bound
that is independent of the transmit power. First, a spectral efficiency upper
bound is established for systems that rely on pilot-assisted channel
estimation; in this framework, cooperation is shown to be possible only within
clusters of limited size, which are subject to out-of-cluster interference
whose power scales with that of the in-cluster signals. Second, an upper bound
is also shown to exist when cooperation is through noncoherent communication;
thus, the spectral efficiency limitation is not a by-product of the reliance on
pilot-assisted channel estimation. Consequently, existing literature that
routinely assumes the high-power spectral efficiency scales with the log of the
transmit power provides only a partial characterization. The complete
characterization proposed in this paper subdivides the high-power regime into a
degrees-of-freedom regime, where the scaling with the log of the transmit power
holds approximately, and a saturation regime, where the spectral efficiency
hits a ceiling that is independent of the power. Using a cellular system as an
example, it is demonstrated that the spectral efficiency saturates at power
levels of operational relevance.Comment: 27 page
Optimal overhead selection for interference alignment in time-varying two-user MIMO X channel
Channel state information (CSI) at the transmitter and receiver is an essential requirement for interference alignment (IA) schemes. For moving users the channel coefficients vary with time and, therefore, it is required to update CSI both at the transmitter and receiver at regular intervals. Meanwhile it is important to note that frequent updates of CSI will reduce data rate and delayed updates will cause a large variation in CSI. In this context we explore the error performance of IA in two-user multiple-input multiple-output (MIMO) X channel where the channel suffers continuous time-varying fading. The bit error rate (BER) performance of MIMO two-user X channel is evaluated for different Doppler frequencies. We also propose a method for calculating optimal pilot overhead for time-varying channels by setting an upper bound on BER
Multi-carrier transmission techniques toward flexible and efficient wireless communication systems
制度:新 ; 文部省報告番号:甲2562号 ; 学位の種類:博士(国際情報通信学) ; 授与年月日:2008/3/15 ; 早大学位記番号:新470
Interference Alignment — Practical Challenges and Test-bed Implementation
Data traffic over wireless communication networks has experienced a
tremendous growth in the last decade, and it is predicted to exponentially
increase in the next decades. Enabling future wireless networks to fulfill this
expectation is a challenging task both due to the scarcity of radio resources
(e.g. spectrum and energy), and also the inherent characteristics of the
wireless transmission medium. Wireless transmission is in general subject to
two phenomena: fading and interference. The elegant interference alignment
concept reveals that with proper transmission signalling design, different
interference signals can in fact be aligned together, such that more radio
resources can be assigned to the desired transmission. Although interference
alignment can achieve a larger data rate compared to orthogonal transmission
strategies, several challenges should be addressed to enable the deployment of
this technique in future wireless networks For instance, to perform
interference alignment, normally, global channel state information (CSI) is
required to be perfectly known at all terminals. Clearly, acquiring such
channel knowledge is a challenging problem in practice and proper channel
training and channel state feedback techniques need to be deployed. In
addition, since the channels are time-varying proper adaptive transmission is
needed. This chapter review recent advances in practical aspects of
interference alignment. It also presents recent test-bed implementations of
signal processing algorithms for the realization of interference alignment.Comment: Book Chapter accepted for publication in the book entitled:
Contemporary Issues in Wireless Communications, ISBN: 978-953-51-4101-3,
Khatib, M. (Ed.), to be published by INTECH Publishers. Expected month of
publication: November 201
Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays
Massive MIMO (multiple-input multiple-output) is no longer a "wild" or
"promising" concept for future cellular networks - in 2018 it became a reality.
Base stations (BSs) with 64 fully digital transceiver chains were commercially
deployed in several countries, the key ingredients of Massive MIMO have made it
into the 5G standard, the signal processing methods required to achieve
unprecedented spectral efficiency have been developed, and the limitation due
to pilot contamination has been resolved. Even the development of fully digital
Massive MIMO arrays for mmWave frequencies - once viewed prohibitively
complicated and costly - is well underway. In a few years, Massive MIMO with
fully digital transceivers will be a mainstream feature at both sub-6 GHz and
mmWave frequencies. In this paper, we explain how the first chapter of the
Massive MIMO research saga has come to an end, while the story has just begun.
The coming wide-scale deployment of BSs with massive antenna arrays opens the
door to a brand new world where spatial processing capabilities are
omnipresent. In addition to mobile broadband services, the antennas can be used
for other communication applications, such as low-power machine-type or
ultra-reliable communications, as well as non-communication applications such
as radar, sensing and positioning. We outline five new Massive MIMO related
research directions: Extremely large aperture arrays, Holographic Massive MIMO,
Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive
MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin
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