In this paper, we consider user scheduling and power allocation techniques for downlinks where transmitted message must be kept confidential from all other unintended users and the number of users is larger than that of access point (AP) antennas. In order to maximize network secrecy rate with a limited number of antennas, the AP schedules a user who can achieve the largest secrecy rate and exploits multiple antennas for transmitting artificial noise to the unintended users. We derive the closed-form expressions of the optimal power allocation for the artificial noise and the average network secrecy rate through asymptotic analysis. The analysis results provide the insightful information on the behaviors of the user scheduling and the effect of system parameters on the network secrecy rate performance. It is shown that opportunistic scheduling with artificial noise transmission technique is more effective than the conventional precoding techniques for multiple confidential message transmissions in terms of network secrecy rate. Furthermore, we have also discussed a transmission strategy for the worst case scenarios where all unintended users are treated as colluding eavesdroppers. The simulations confirm the validity of the analysis results and provide additional information on the network performance in general cases.

This paper investigates optimal content placement for wireless femto-caching network. The average bit error rate (BER) is formulated as a function of content placement under wireless fading. To minimize the average BER, we propose a greedy algorithm finding optimal content placement with low-computational complexity. Exploiting the property of the optimal content placement which we derive, the proposed algorithm can be performed over considerably reduced search space. Contrary to the optimal content placement without consideration of wireless fading aspects, we reveal that optimal content placement can be reached by balancing a tradeoff between two different gains: file diversity gain and channel diversity gain. Moreover, we also identify the conditions that the optimal placement can be found without running the proposed greedy algorithm and derive the corresponding optimal content placement in closed form.

This paper considers a cell with many caching helpers, such as femto-base stations with memories for caching files. We formulate average bit error rate (BER) as a function of caching placement in a Rayleigh flat fading channel. In order to minimize the average BER, we propose an algorithm which finds a caching placement in greedy way and prove that the caching placement found by the proposed greedy algorithm is optimal. We also show that the proposed greedy algorithm has complexity independent of file library size. It is shown that the optimal caching placement is not just caching all different files; however, for a given environment, the optimal caching placement is to balance between channel diversity gain achieved by caching the same file in multiple helpers and caching diversity gain achieved by caching different files in helpers to enlarge a set of cached-file.

In machine-to-machine communications, several machines located close to one another can form a cluster to leverage spatial reuse gains and energy savings. We investigate a machine selection algorithm where only a machine in each cluster transfers its data to the cellular user via device-to-device communication and then the cellular user forwards it to the base station. Unlike the previous works that focus on data rate or channel condition as the selection metrics, this paper proposes a correlation-aware selection algorithm which maximizes the joint entropy extracted from the data delivered from the selected machines. Our evaluation results show the proposed selection scheme reaps a significant gain and is near-optimal.

This paper investigates device-to-device (D2D) communication nested in a cellular network, where a pair of D2D users directly exchanges their information using the uplink frequency band of the cellular network. When the D2D user treats the interference from the cellular user as noise, power control at the cellular user is optimal for maximizing the rate of the cellular user while controlling the interference to the D2D user. However, if the D2D user can perform successive interference cancelation (SIC), the cellular user needs to adjust both transmit power and rate to maximize its rate, because the decodability of the interfering signals at the D2D user depends not only on the signal power but also on the rate of the cellular user. To control the interference from the cellular user, we propose a joint transmit power and rate control scheme at the cellular user. Forcing the cellular user to transmit with a reduced data rate compared with the maximum possible rate, given its transmit power, the proposed joint power and rate control scheme efficiently enables SIC at the D2D user. To reduce the computational complexity, we also propose a near-optimal scheme that employs either power control or rate control depending on the channel conditions.

This paper proposes a user cooperation scheme to improve the achievable rate of a cell edge user in a two cell model. In the proposed user cooperation, one user helps decoding of the other user by either desired signal forwarding (SF) or interference forwarding (IF). We derive an achievable rate region of the proposed user cooperation and compare it with that of a conventional two-cell system without user cooperation. It is shown that the proposed user cooperation exploiting either SF or IF is beneficial in terms of achievable rate region compared to the conventional two-cell system.

We characterize the Pareto boundary of the achievable rate region of the two-user symmetric Gaussian interference channel when transmitters control their transmission power and receivers have successive interference cancellation capability. By identifying the shape of achievable rate region according to the strength of interference channels, we find combinations of decoding and power allocation strategies achieving the Pareto boundary. We also characterize the Pareto boundary of the achievable rate region when time sharing is additionally considered.

Cognitive radio (CR) systems are typically classified into two types. In overlay CR, a secondary user opportunistically accesses primary user's spectrum when it is unused, while a secondary user in underlay CR accesses the spectrum at any time as long as the interference power received at a primary user is below a certain level. This paper investigates a hybrid CR system where a secondary user probabilistically changes its spectrum access mode for secondary user's throughput maximization while guaranteeing primary user's target throughput. Basically, the hybrid CR works like overlay CR. The secondary user constantly monitors activity of the primary user and transmits data with maximum transmit power if transmission of the primary user is not detected. However, the only difference from overlay CR is that even when transmission of the primary user is detected, the secondary users are able to access the spectrum with regulated low transmit power with switching rate c. We show that there is a trade-off of increasing c due to recursive interactions between primary and secondary users, and optimizing c is crucial to balance the gain and loss of secondary user's underlay spectrum access. The proposed hybrid CR is shown to achieve higher throughput and be more robust to detection errors than conventional CR systems.