252 research outputs found
M. Chiani, D. Dardari, and M. K. Simon, “New exponential bounds and approximations for the computation of error probability in fading channels,” IEEE Trans. Wireless Commun., vol. 2, no. 4, pp. 840 – 845, Jul. 2003.
M. Chiani, D. Dardari, and M. K. Simon, “New exponential bounds and approximations for the computation of error probability in fading channels,” IEEE Trans. Wireless Commun., vol. 2, no. 4, pp. 840 – 845, Jul. 2003.
Distribution of the largest root of a matrix for Roy's test in multivariate analysis of variance
Let denote two independent real Gaussian and matrices with , each constituted by zero mean i.i.d. columns with
common covariance. The Roy's largest root criterion, used in multivariate
analysis of variance (MANOVA), is based on the statistic of the largest
eigenvalue, , of , where
and are independent central Wishart matrices. We derive a new
expression and efficient recursive formulas for the exact distribution of
. The expression can be easily calculated even for large parameters,
eliminating the need of pre-calculated tables for the application of the Roy's
test
M. Chiani “Introducing erasures in decision-feedback equalization to reduce error propagation,” IEEE Trans. Commun., vol. 45, no. 7, pp. 757–760, Jul. 1997.
High-Throughput Random Access via Codes on Graphs
Recently, contention resolution diversity slotted ALOHA (CRDSA) has been
introduced as a simple but effective improvement to slotted ALOHA. It relies on
MAC burst repetitions and on interference cancellation to increase the
normalized throughput of a classic slotted ALOHA access scheme. CRDSA allows
achieving a larger throughput than slotted ALOHA, at the price of an increased
average transmitted power. A way to trade-off the increment of the average
transmitted power and the improvement of the throughput is presented in this
paper. Specifically, it is proposed to divide each MAC burst in k sub-bursts,
and to encode them via a (n,k) erasure correcting code. The n encoded
sub-bursts are transmitted over the MAC channel, according to specific
time/frequency-hopping patterns. Whenever n-e>=k sub-bursts (of the same burst)
are received without collisions, erasure decoding allows recovering the
remaining e sub-bursts (which were lost due to collisions). An interference
cancellation process can then take place, removing in e slots the interference
caused by the e recovered sub-bursts, possibly allowing the correct decoding of
sub-bursts related to other bursts. The process is thus iterated as for the
CRDSA case.Comment: Presented at the Future Network and MobileSummit 2010 Conference,
Florence (Italy), June 201
Coded Slotted ALOHA: A Graph-Based Method for Uncoordinated Multiple Access
In this paper, a random access scheme is introduced which relies on the
combination of packet erasure correcting codes and successive interference
cancellation (SIC). The scheme is named coded slotted ALOHA. A bipartite graph
representation of the SIC process, resembling iterative decoding of generalized
low-density parity-check codes over the erasure channel, is exploited to
optimize the selection probabilities of the component erasure correcting codes
via density evolution analysis. The capacity (in packets per slot) of the
scheme is then analyzed in the context of the collision channel without
feedback. Moreover, a capacity bound is developed and component code
distributions tightly approaching the bound are derived.Comment: The final version to appear in IEEE Trans. Inf. Theory. 18 pages, 10
figure
MIMO Networks: the Effects of Interference
Multiple-input/multiple-output (MIMO) systems promise enormous capacity
increase and are being considered as one of the key technologies for future
wireless networks. However, the decrease in capacity due to the presence of
interferers in MIMO networks is not well understood. In this paper, we develop
an analytical framework to characterize the capacity of MIMO communication
systems in the presence of multiple MIMO co-channel interferers and noise. We
consider the situation in which transmitters have no information about the
channel and all links undergo Rayleigh fading. We first generalize the known
determinant representation of hypergeometric functions with matrix arguments to
the case when the argument matrices have eigenvalues of arbitrary multiplicity.
This enables the derivation of the distribution of the eigenvalues of Gaussian
quadratic forms and Wishart matrices with arbitrary correlation, with
application to both single user and multiuser MIMO systems. In particular, we
derive the ergodic mutual information for MIMO systems in the presence of
multiple MIMO interferers. Our analysis is valid for any number of interferers,
each with arbitrary number of antennas having possibly unequal power levels.
This framework, therefore, accommodates the study of distributed MIMO systems
and accounts for different positions of the MIMO interferers.Comment: Submitted to IEEE Trans. on Info. Theor
A Decoding Algorithm for LDPC Codes Over Erasure Channels with Sporadic Errors
none4An efficient decoding algorithm for low-density parity-check (LDPC) codes on erasure channels with sporadic errors (i.e., binary error-and-erasure channels with error probability much smaller than the erasure probability) is proposed and its performance analyzed. A general single-error multiple-erasure (SEME) decoding algorithm is first described, which may be in principle used with any binary linear block code. The algorithm is optimum whenever the non-erased part of the received word is affected by at most one error, and is capable of performing error detection of multiple errors. An upper bound on the average block error probability under SEME decoding is derived for the linear random code ensemble. The bound is tight and easy to implement. The algorithm is then adapted to LDPC codes, resulting in a simple modification to a previously proposed efficient maximum likelihood LDPC erasure decoder which exploits the parity-check matrix sparseness. Numerical results reveal that LDPC codes under efficient SEME decoding can closely approach the average performance of random codes.noneG. Liva; E. Paolini; B. Matuz; M. ChianiG. Liva; E. Paolini; B. Matuz; M. Chian
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