Saddle point problems arise from many wireless applications, and primal-dual
iterative algorithms are widely applied to find the saddle points. In the
existing literature, the convergence results of such algorithms are established
assuming the problem specific parameters remain unchanged during the
iterations. However, this assumption is unrealistic in time varying wireless
systems, as explicit message passing is usually involved in the iterations and
the channel state information (CSI) may change in a time scale comparable to
the algorithm update period.

In this paper, we consider a queue-aware distributive resource control
algorithm for two-hop MIMO cooperative systems. We shall illustrate that relay
buffering is an effective way to reduce the intrinsic half-duplex penalty in
cooperative systems. The complex interactions of the queues at the source node
and the relays are modeled as an average-cost infinite horizon Markov Decision
Process (MDP). The traditional approach solving this MDP problem involves
centralized control with huge complexity.

Rank-constrained optimization problems have received an increasing intensity
of interest recently, because many optimization problems in communications and
signal processing applications can be cast into a rank-constrained optimization
problem. However, due to the non-convex nature of rank constraints, a
systematic solution to general rank-constrained problems has remained open for
a long time. In this paper, we focus on a rank-constrained optimization problem
with a Schur-convex/concave objective function and multiple
trace/logdeterminant constraints.

In this paper, we consider a two-hop relay-assisted cognitive downlink OFDMA
system (named as secondary system) dynamically accessing a spectrum licensed to
a primary network, thereby improving the efficiency of spectrum usage. A
cluster-based relay-assisted architecture is proposed for the secondary system,
where relay stations are employed for minimizing the interference to the users
in the primary network and achieving fairness for cell-edge users.

Transmit beamforming is a simple multi-antenna technique for increasing
throughput and the transmission range of a wireless communication system. The
required feedback of channel state information (CSI) can potentially result in
excessive overhead especially for high mobility or many antennas. This work
concerns efficient feedback for transmit beamforming and establishes a new
approach of controlling feedback for maximizing net throughput, defined as
throughput minus average feedback cost.

In this paper, we consider the delay-sensitive power and transmission
threshold control design in S-ALOHA network with FSMC fading channels. The
random access system consists of an access point with K competing users, each
has access to the local channel state information (CSI) and queue state
information (QSI) as well as the common feedback (ACK/NAK/Collision) from the
access point. We seek to derive the delay-optimal control policy (composed of
threshold and power control).