14,673 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
Space Division Multiple Access with a Sum Feedback Rate Constraint
On a multi-antenna broadcast channel, simultaneous transmission to multiple
users by joint beamforming and scheduling is capable of achieving high
throughput, which grows double logarithmically with the number of users. The
sum rate for channel state information (CSI) feedback, however, increases
linearly with the number of users, reducing the effective uplink capacity. To
address this problem, a novel space division multiple access (SDMA) design is
proposed, where the sum feedback rate is upper-bounded by a constant. This
design consists of algorithms for CSI quantization, threshold based CSI
feedback, and joint beamforming and scheduling. The key feature of the proposed
approach is the use of feedback thresholds to select feedback users with large
channel gains and small CSI quantization errors such that the sum feedback rate
constraint is satisfied. Despite this constraint, the proposed SDMA design is
shown to achieve a sum capacity growth rate close to the optimal one. Moreover,
the feedback overflow probability for this design is found to decrease
exponentially with the difference between the allowable and the average sum
feedback rates. Numerical results show that the proposed SDMA design is capable
of attaining higher sum capacities than existing ones, even though the sum
feedback rate is bounded.Comment: 29 pages; submitted to IEEE Transactions on Signal Processin
Radioisotope thermionic power supply for spacecraft
Power supply design for unmanned electric propulsion missions to outer planets utilizes a store of curium-244 in compact array of capsules as energy source. Supply subassemblies are: heat source, converter equipment which supplies power, and safety equipment. System is designed for a 72,000 hour mission
Performance of Orthogonal Beamforming for SDMA with Limited Feedback
On the multi-antenna broadcast channel, the spatial degrees of freedom
support simultaneous transmission to multiple users. The optimal multiuser
transmission, known as dirty paper coding, is not directly realizable.
Moreover, close-to-optimal solutions such as Tomlinson-Harashima precoding are
sensitive to CSI inaccuracy. This paper considers a more practical design
called per user unitary and rate control (PU2RC), which has been proposed for
emerging cellular standards. PU2RC supports multiuser simultaneous
transmission, enables limited feedback, and is capable of exploiting multiuser
diversity. Its key feature is an orthogonal beamforming (or precoding)
constraint, where each user selects a beamformer (or precoder) from a codebook
of multiple orthonormal bases. In this paper, the asymptotic throughput scaling
laws for PU2RC with a large user pool are derived for different regimes of the
signal-to-noise ratio (SNR). In the multiuser-interference-limited regime, the
throughput of PU2RC is shown to scale logarithmically with the number of users.
In the normal SNR and noise-limited regimes, the throughput is found to scale
double logarithmically with the number of users and also linearly with the
number of antennas at the base station. In addition, numerical results show
that PU2RC achieves higher throughput and is more robust against CSI
quantization errors than the popular alternative of zero-forcing beamforming if
the number of users is sufficiently large.Comment: 27 pages; to appear in IEEE Transactions on Vehicular Technolog
MIMO Interference Alignment Over Correlated Channels with Imperfect CSI
Interference alignment (IA), given uncorrelated channel components and
perfect channel state information, obtains the maximum degrees of freedom in an
interference channel. Little is known, however, about how the sum rate of IA
behaves at finite transmit power, with imperfect channel state information, or
antenna correlation. This paper provides an approximate closed-form
signal-to-interference-plus-noise-ratio (SINR) expression for IA over
multiple-input-multiple-output (MIMO) channels with imperfect channel state
information and transmit antenna correlation. Assuming linear processing at the
transmitters and zero-forcing receivers, random matrix theory tools are
utilized to derive an approximation for the post-processing SINR distribution
of each stream for each user. Perfect channel knowledge and i.i.d. channel
coefficients constitute special cases. This SINR distribution not only allows
easy calculation of useful performance metrics like sum rate and symbol error
rate, but also permits a realistic comparison of IA with other transmission
techniques. More specifically, IA is compared with spatial multiplexing and
beamforming and it is shown that IA may not be optimal for some performance
criteria.Comment: 21 pages, 7 figures, submitted to IEEE Transactions on Signal
Processin
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