Wireless network virtualization is a promising solution to enable sharing of spectrum resources for future explosive demands in wireless communications. In this paper, we consider a resource allocation problem for an infrastructure provider (InP) to efficiently embed wireless virtual networks that are requested from multiple virtual network operators, who share the same physical substrate owned by the InP. Different from previous works, we consider the possibility of partially available spectrum band and the capability of spectrum aggregation (SA). The resource allocation problem is formulated as an integer optimization problem, and a heuristic algorithm based on the Bottom-Left (BL) algorithm is proposed to tackle the problem. We show that the resource utilization is increased with spectrum aggregation and the superior performance of our proposed algorithm.

In this paper, we consider a jamming game in wireless networks in which a malicious user tries to jam the transmissions of a user in Gaussian fading multichannel. Both the user and the jammer allocate power to multiple channels with their total power constraints in order to maximize their utilities. We model the utility of the user as a weighted sum of successfully received packets on all channels, and the goal of the jammer is trying to minimize the user's utility. The power allocation strategies at Nash equilibrium of this zero-sum game are derived in closed form and some properties of robustness and worst-case guarantee are presented.

In this paper, we analytically study a random access network that uses the request-to-send and clear-to-send (RTS/CTS) handshake for reservation of transmission time. In the network, nodes initiate data transmission to a common base station (BS) by sending an RTS packet according to a transmission probability. The RTS packet of a node specifies the length of the node's requested data transmission interval, and will be successfully received by the BS if its signal to interference plus noise ratio (SINR) is higher than the capture ratio. The BS will then reply with a CTS packet to grant this node the requested data transmission interval and inform the other nodes not to interrupt. The transmission probabilities of RTS packets of all nodes will determine the average throughput and power consumption of each node. The set of all possible throughputs that can be achieved by the network is called the throughput region. We characterize the throughput region and provide an upper bound on the total transmission power consumption over the throughput region at the optimal operating point. Specifically, the upper bound corresponds to one of three points in the throughput region depending on the fraction of time occupied by the RTS packets.

In this paper, we consider a channel-aware ALOHA network in which users have the knowledge of their own channel state information (CSI) and exploit this decentralized CSI by utilizing CSI-based transmission schemes. The system throughput is investigated with multi-region transmission schemes under the signal-to-interference-plus-noise ratio (SINR) capture model. We discover that the two-region transmission scheme performs well enough for maximizing the throughput.

We consider an ALOHA network in which users have the knowledge of their own channel state information (CSI). In each time slot, each user transmits its packet to the base station (BS) according to a CSI-dependent transmission scheme. A packet is successfully received if its signal to interference plus noise ratio (SINR) is larger than the capture ratio. We analyze the throughput of this network under a threshold-based transmission scheme in which a user transmits only when its channel gain is higher than a threshold. It is shown that in some cases the conventional ALOHA transmission scheme without CSI may outperform the threshold-based transmission scheme in terms of the maximum possible throughput. We give the condition for this phenomenon and find that this phenomenon will not occur if the BS is capable of receiving three or more packets simultaneously. Besides, we present a transmission scheme in which a user only transmits when its channel gain lies in an interval. This scheme includes the threshold-based one as a special case.

In this paper, we study the spectrum access problem in cognitive radio networks with the objective to maximize the expected throughput of cognitive users. We show that the performance of a uniform access policy that uniformly selects one channel to sense, independent of the primary users' behaviors on the channels, is close to that of the optimal randomized access policy when there are a large number of contending cognitive users. We also characterize the throughput taking the energy constraint of cognitive users into account, and present a unified PHY/MAC design to improve the throughput.

In this paper, we consider the problem of power level selections under an average power constraint in slotted ALOHA networks. In the network, each node chooses a power level from a pre-determined power level set based on a probability for each access attempt. The derivation of the probability for maximizing the throughput is difficult. In addition, nodes may not always obey the given algorithm in a distributed network because a misbehaving node might gain better performance at the expense of the others. To prevent the potential of misbehavior, we derive a cheat-proof algorithm based on game theory, which will make no nodes in the network want to deviate from the algorithm. Further, we show the throughput loss of the cheat-proof algorithm compared to the optimal one, and show the occurrence of unjust situation if the property of cheat-proof is not taken into account.

We derive both the optimal and the game-theoretic (cheat-proof) solutions in closed form, to a problem of distributed access with power control in a pairwise interaction network. In this network, each node has an energy constraint in a fixed time unit for using different power levels in each access attempt competing with a randomly selected node. The one with larger power level wins the access. The optimal control for nodes in the network to maximize the number of wining the access as well as the game-theoretic (cheat-proof) control in which no one will deviate to attain higher number of wining the access are fully characterized in this paper.

We characterize the Nash equilibrium point of the request probability in a network using the Request-to-send / Clear-to-send (RTS/CTS) handshake mechanism for channel reservation, where each node tries to minimize its average power investment selfishly while meeting its average throughput demand over the shared wireless channel to a common base station. The feasible region of throughput demands is then maximized by the optimal data transmission periods and meanwhile the average power investment at the better Nash equilibrium is reduced. In addition, the performance of the optimum design is compared to that in a network without the RTS/CTS handshake mechanism.

We study a class of space-time codes constructed by linear dispersion encoding that allow low-complexity linear minimum mean square error (MMSE) decoding for a multiple access system. Considering that the information symbols are drawn from square QAM constellations, we optimize rate-one space time code designs with MMSE decoding to achieve minimum bit error rate (BER) for any channel realization. In addition, the performance is further improved with a simple MMSE successive interference cancellation (MMSE-SIC) method. Simulation results compare the proposed design with existing rate-one designs and show that simple rate-one circulant designs are also good candidates for deployment in multiple access systems.

We explicitly construct space-time codes for a multiple access system composed of K users transmitting simultaneously to the base station in block-fading channels. Each user encodes its own data independently without cooperation between users. Our codes design uses the idea of linear dispersion encoding together with circulant matrices assigned to each user that allow low-complexity linear minimum mean square error (MMSE) decoding when the channel realization is known to the base station. Moreover, the ergodic sum rate of the proposed design is studied and compared with the sum capacity.