195 research outputs found
How much feedback is required in MIMO Broadcast Channels?
In this paper, a downlink communication system, in which a Base Station (BS)
equipped with M antennas communicates with N users each equipped with K receive
antennas (), is considered. It is assumed that the receivers have
perfect Channel State Information (CSI), while the BS only knows the partial
CSI, provided by the receivers via feedback. The minimum amount of feedback
required at the BS, to achieve the maximum sum-rate capacity in the asymptotic
case of and different ranges of SNR is studied. In the fixed and
low SNR regimes, it is demonstrated that to achieve the maximum sum-rate, an
infinite amount of feedback is required. Moreover, in order to reduce the gap
to the optimum sum-rate to zero, in the fixed SNR regime, the minimum amount of
feedback scales as , which is achievable by the Random
Beam-Forming scheme proposed in [14]. In the high SNR regime, two cases are
considered; in the case of , it is proved that the minimum amount of
feedback bits to reduce the gap between the achievable sum-rate and the maximum
sum-rate to zero grows logaritmically with SNR, which is achievable by the
"Generalized Random Beam-Forming" scheme, proposed in [18]. In the case of , it is shown that by using the Random Beam-Forming scheme and the total
amount of feedback not growing with SNR, the maximum sum-rate capacity is
achieved.Comment: Submitted to IEEE Trans. on Inform. Theor
Rate-Constrained Wireless Networks with Fading Channels: Interference-Limited and Noise-Limited Regimes
A network of wireless communication links is considered in a Rayleigh
fading environment. It is assumed that each link can be active and transmit
with a constant power or remain silent. The objective is to maximize the
number of active links such that each active link can transmit with a constant
rate . An upper bound is derived that shows the number of active links
scales at most like . To obtain a lower bound, a
decentralized link activation strategy is described and analyzed. It is shown
that for small values of , the number of supported links by this
strategy meets the upper bound; however, as grows, this number
becomes far below the upper bound. To shrink the gap between the upper bound
and the achievability result, a modified link activation strategy is proposed
and analyzed based on some results from random graph theory. It is shown that
this modified strategy performs very close to the optimum. Specifically, this
strategy is \emph{asymptotically almost surely} optimum when
approaches or 0. It turns out the optimality results are obtained in
an interference-limited regime. It is demonstrated that, by proper selection of
the algorithm parameters, the proposed scheme also allows the network to
operate in a noise-limited regime in which the transmission rates can be
adjusted by the transmission powers. The price for this flexibility is a
decrease in the throughput scaling law by a multiplicative factor of .Comment: Submitted to IEEE Trans. Information Theor
Media-Based MIMO: A New Frontier in Wireless Communications
The idea of Media-based Modulation (MBM), is based on embedding information
in the variations of the transmission media (channel state). This is in
contrast to legacy wireless systems where data is embedded in a Radio Frequency
(RF) source prior to the transmit antenna. MBM offers several advantages vs.
legacy systems, including "additivity of information over multiple receive
antennas", and "inherent diversity over a static fading channel". MBM is
particularly suitable for transmitting high data rates using a single transmit
and multiple receive antennas (Single Input-Multiple Output Media-Based
Modulation, or SIMO-MBM). However, complexity issues limit the amount of data
that can be embedded in the channel state using a single transmit unit. To
address this shortcoming, the current article introduces the idea of Layered
Multiple Input-Multiple Output Media-Based Modulation (LMIMO-MBM). Relying on a
layered structure, LMIMO-MBM can significantly reduce both hardware and
algorithmic complexities, as well as the training overhead, vs. SIMO-MBM.
Simulation results show excellent performance in terms of Symbol Error Rate
(SER) vs. Signal-to-Noise Ratio (SNR). For example, a LMIMO-MBM is
capable of transmitting bits of information per (complex) channel-use,
with SER at dB (or SER
at dB). This performance is achieved using a single transmission
and without adding any redundancy for Forward-Error-Correction (FEC). This
means, in addition to its excellent SER vs. energy/rate performance, MBM
relaxes the need for complex FEC structures, and thereby minimizes the
transmission delay. Overall, LMIMO-MBM provides a promising alternative to MIMO
and Massive MIMO for the realization of 5G wireless networks.Comment: 26 pages, 11 figures, additional examples are given to further
explain the idea of Media-Based Modulation. Capacity figure adde
Communication Over MIMO Broadcast Channels Using Lattice-Basis Reduction
A simple scheme for communication over MIMO broadcast channels is introduced
which adopts the lattice reduction technique to improve the naive channel
inversion method. Lattice basis reduction helps us to reduce the average
transmitted energy by modifying the region which includes the constellation
points. Simulation results show that the proposed scheme performs well, and as
compared to the more complex methods (such as the perturbation method) has a
negligible loss. Moreover, the proposed method is extended to the case of
different rates for different users. The asymptotic behavior of the symbol
error rate of the proposed method and the perturbation technique, and also the
outage probability for the case of fixed-rate users is analyzed. It is shown
that the proposed method, based on LLL lattice reduction, achieves the optimum
asymptotic slope of symbol-error-rate (called the precoding diversity). Also,
the outage probability for the case of fixed sum-rate is analyzed.Comment: Submitted to IEEE Trans. on Info. Theory (Jan. 15, 2006), Revised
(Jun. 12, 2007
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