32,390 research outputs found
Asymptotically Optimal Multiple-access Communication via Distributed Rate Splitting
We consider the multiple-access communication problem in a distributed
setting for both the additive white Gaussian noise channel and the discrete
memoryless channel. We propose a scheme called Distributed Rate Splitting to
achieve the optimal rates allowed by information theory in a distributed
manner. In this scheme, each real user creates a number of virtual users via a
power/rate splitting mechanism in the M-user Gaussian channel or via a random
switching mechanism in the M-user discrete memoryless channel. At the receiver,
all virtual users are successively decoded. Compared with other multiple-access
techniques, Distributed Rate Splitting can be implemented with lower complexity
and less coordination. Furthermore, in a symmetric setting, we show that the
rate tuple achieved by this scheme converges to the maximum equal rate point
allowed by the information-theoretic bound as the number of virtual users per
real user tends to infinity. When the capacity regions are asymmetric, we show
that a point on the dominant face can be achieved asymptotically. Finally, when
there is an unequal number of virtual users per real user, we show that
differential user rate requirements can be accommodated in a distributed
fashion.Comment: Submitted to the IEEE Transactions on Information Theory. 15 Page
On multiple access random medium access control
In this paper, we develop a new class of medium access control protocol, which allows each user to transmit at different data rates chosen randomly from an appropriately determined set of rates. By using successive interference cancellation, multiple packets can be received simultaneously. In slotted Aloha type Gaussian networks, we show that the achievable total throughput of the proposed protocol is at least a constant fraction of the mac sum rate when the number of transmission rates at each node is equal to the number of users in the network. We also study the case when only a limited number of transmission rates is available at each node. Extension to rate splitting is discussed. Simulation results show that the proposed protocol can achieve a significant throughput gain over the conventional Aloha
Gaussian Multiple Access via Compute-and-Forward
Lattice codes used under the Compute-and-Forward paradigm suggest an
alternative strategy for the standard Gaussian multiple-access channel (MAC):
The receiver successively decodes integer linear combinations of the messages
until it can invert and recover all messages. In this paper, a multiple-access
technique called CFMA (Compute-Forward Multiple Access) is proposed and
analyzed. For the two-user MAC, it is shown that without time-sharing, the
entire capacity region can be attained using CFMA with a single-user decoder as
soon as the signal-to-noise ratios are above . A partial analysis
is given for more than two users. Lastly the strategy is extended to the
so-called dirty MAC where two interfering signals are known non-causally to the
two transmitters in a distributed fashion. Our scheme extends the previously
known results and gives new achievable rate regions.Comment: to appear in IEEE Transactions on Information Theor
Fairness in Multiuser Systems with Polymatroid Capacity Region
For a wide class of multi-user systems, a subset of capacity region which
includes the corner points and the sum-capacity facet has a special structure
known as polymatroid. Multiaccess channels with fixed input distributions and
multiple-antenna broadcast channels are examples of such systems. Any interior
point of the sum-capacity facet can be achieved by time-sharing among corner
points or by an alternative method known as rate-splitting. The main purpose of
this paper is to find a point on the sum-capacity facet which satisfies a
notion of fairness among active users. This problem is addressed in two cases:
(i) where the complexity of achieving interior points is not feasible, and (ii)
where the complexity of achieving interior points is feasible. For the first
case, the corner point for which the minimum rate of the active users is
maximized (max-min corner point) is desired for signaling. A simple greedy
algorithm is introduced to find the optimum max-min corner point. For the
second case, the polymatroid properties are exploited to locate a rate-vector
on the sum-capacity facet which is optimally fair in the sense that the minimum
rate among all users is maximized (max-min rate). In the case that the rate of
some users can not increase further (attain the max-min value), the algorithm
recursively maximizes the minimum rate among the rest of the users. It is shown
that the problems of deriving the time-sharing coefficients or rate-spitting
scheme can be solved by decomposing the problem to some lower-dimensional
subproblems. In addition, a fast algorithm to compute the time-sharing
coefficients to attain a general point on the sum-capacity facet is proposed.Comment: Submitted To IEEE Transactions on Information Theory, June 200
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