In the Embedded Signal Processing Laboratory,
we have completed research in the following topics in
our work in OFDM basesation design has focused on the following:
Broadband wireless system standards, e.g. IEEE 802.16e and Third Generation
Partnership Project (3GPP) Long Term Evolution (LTE), consider Orthogonal
Frequency Division Multiple Access (OFDMA) as the preferred physical layer
multiple access scheme, esp. for the downlink.
Due to the limited resources available at the basestation, e.g. bandwidth
and power, intelligent allocation of these resources to the users is crucial
for delivering the best possible quality of service to the consumer with the
The problem of allocating subcarriers, rates, and powers to the
different users in an OFDMA system has been an area of active research.
Due to the discrete decisions required in assigning only one user to
each subcarrier, this problem is combinatorial in nature and is very
difficult to solve optimally. Thus, previous research efforts in OFDMA
resource allocation have typically focused on:
Our work, on the other hand, addresses the aforementioned shortcomings by:
- Maximizing instantaneous performance: The allocation decisions
are performed for the current time instant subject to the current
resource constraints. Hence, the time-varying nature of the wireless
channel is not exploited to improve the performance of the system.
- Developing heuristic sub-optimal algorithms: A popular approach
in previous works to achieve near-optimal performance requires solving a
large constrained convex optimization problem, which is too complex for
real-time implementation. Hence, the focus has been on developing
sub-optimal heuristic algorithms typically with quadratic complexity and
no performance guarantees.
- Assuming the availability of perfect channel state information
(CSI): Since allocation decisions are made based on CSI feedback from
the users, this assumption is unrealistic due to channel estimation
errors and feedback delay.
In summary, our work attempts to dispel the myth that OFDMA resource
allocation is too complex to solve optimally, even when considering
average performance and assuming imperfect CSI.
- Maximizing average performance: We perform OFDMA resource
allocation considering the expected performance by using the statistics
of the wireless channel, allowing us to exploit temporal diversity, in
addition to frequency and multi-user diversity. We propose algorithms
for both continuous and discrete rate systems.
- Developing algorithms based on dual optimization techniques: We
develop algorithms based on a dual optimization framework that have
complexities that are linear in the number of subcarriers and users, and
that achieve solutions that are guaranteed to be within 99.9999% of the
optimal solution in typical scenarios.
- Assuming the availability of imperfect CSI: We assume that only
imperfect CSI acquired through channel estimation and prediction is
available. Thus, our allocation decisions are made while explicitly
considering the error statistics of the imperfect CSI.
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