This paper analyzes the achievable secrecy transmission rates (STRs) of Alamouti space–time block coding (STBC) with the decision feedback (DF) detection in wiretap time-selective fading channels and studies how to optimally design the Wyner’s codebook to maximize it. Specifically, we derive the STR with both connection outage probability and secrecy outage probability for an arbitrary temporal correlation and find the optimal codeword rate and the secrecy rate to maximize it.

Coded computation has attracted great interests as a promising technique to cope with straggling computing nodes in mobile edge computing (MEC) networks. Contrary to the existing coded computation schemes developed with a fixed network topology, this paper studies a MDS coded computation for random networks. Specifically, we put forth maximum distance separable (MDS) coded task offloading and investigate its MDS coded computing gain by deriving the average successful retrieval probability with stochastic geometry in random wireless edge computing networks, where it encodes the original task into multiple equal and small sized MDS coded sub-tasks and offloads their subset to edge computing nodes for computation. We also identify a tradeoff between the latency in processing a sub-task at an edge node and the minimal number of edge nodes required to retrieve the original task output, according to the size of MDS coded sub-tasks. To efficiently control the tradeoff, we determine the desirable size of MDS coded sub-tasks in a semi-closed form to maximize the average successful retrieval probability for regime 1 and regime 2 networks, which correspond to the cases that communication latency is negligible compared to computation latency and that computation latency is negligible compared to communication latency, respectively, and develop an efficient algorithm with low search complexity for a general environment. Our numerical results reveal that the proposed scheme outperforms the other conventional task offloading schemes such as partial task offloading and replication task offloading in terms of average successful retrieval probability.

Depending on what and how caching helpers cache content in their finite storage, the caching helpers can offer either a content diversity gain by serving diverse content or a cooperative gain by jointly transmitting the same content. This paper identifies a tradeoff between the content diversity gain and the cooperative gain according to content placements and proposes a probabilistic content placement to optimally balance the tradeoff. Using stochastic geometry, we quantify this tradeoff by deriving the cache hit rate and the rate coverage probability. To efficiently control the tradeoff, we determine the near-optimal caching probabilities that maximize the average content delivery success probability with the cooperative caching helpers. Our analysis and numerical results reveal that our proposed content placement outperforms the conventional caching schemes, such as caching with uniform probabilities, caching the most popular contents, and caching the content maximizing the cache hit, in terms of the average content delivery success probability.

From the perspective of a single user, occupying all available radio access technologies (RAT) is always beneficial for increasing data rate. However, due to the interactions among the users, occupying multiple RATs at each user might not be optimal in a network view point. This paper studies the optimal association strategy to maximize the system throughput in multi-RAT cellular networks. To this end, with stochastic geometry, we derive the network sum rates by considering two association modes; single RAT association (altruistic association) and multiple RATs association (selfish association). By comparing the network sum rates for the two association modes, we show that optimally balancing the number of users between two association modes is necessary to improve the performances. With some numerical examples, we investigate how various system parameters, such as the number of carrier components, user density, and density of access points, etc, affect on the optimal portion of the users between two association modes.

Content delivery success in wireless caching helper networks depends mainly on cache-based channel selection diversity and network interference. For given channel fading and network geometry, both channel selection diversity and network interference dynamically vary according to what and how the caching helpers cache at their finite storage space. We study probabilistic content placement (or caching placement) to desirably control cache-based channel selection diversity and network interference in a stochastic wireless caching helper network, with sophisticated considerations of wireless fading channels, interactions among multiple users, such as interference and loads at caching helpers, and arbitrary memory size. Using stochastic geometry, we derive optimal caching probabilities in the closed form to maximize the average success probability of content delivery and propose an efficient algorithm to find the solution in a noise-limited network. In an interference-limited network, based on a lower bound of the average success probability of content delivery, we find near-optimal caching probabilities in the closed form to control the channel selection diversity and the network interference. We numerically verify that the proposed content placement is superior to other comparable content placement strategies.

From the perspective of a single user, concurrent utilization of all available radio access technologies (RATs) is always beneficial for increasing individual data rate. However, given the interactions among users, occupying multiple RATs at each user might not be optimal from a network-wide viewpoint. In this paper, we explore the answer to the posed question what is the optimal access strategy in multi-RAT cellular networks, solving a distributed RAT access control problem for maximizing network throughput. With stochastic geometry, we analytically evaluate network throughputs for two different access modes: 1) single RAT access (altruistic access) and 2) simultaneous multiple RATs access (selfish access). Comparing the network throughputs for the two modes, we first show that the network throughput can be maximized by properly mixing the two access modes and then derive the optimal portions of each mode in a network, which motivates a distributed RAT access control in a probabilistic sense. The optimal mixture of the two modes controls scheduling contention and interference among users to maximize the network throughput. We also analyze the effects of various system parameters, such as the number of frequency sub-bands for each RAT, user density, and access point density, on the optimal portions of the two access modes.

This paper models the cooperative transmission via caching helpers (cache-based joint transmission), which cache one of the K most popular files, in wireless cellular networks and analyzes its performance in terms of the file transmission success probability in the stochastic geometry framework. For given caching placement, the caching helpers can either provide a file diversity gain by serving different files or a cooperative gain by jointly transmitting the same files. In order to account for the tradeoff between the file diversity gain and the cooperative gain, we derive the cache hit probability and the rate coverage probability. We also find the optimal caching placement balancing the tradeoff and investigate the effects of various system parameters, such as the cooperative region, the density of caching helpers, and the file popularity exponent, on the optimal caching placement.

A distributed beamforming technique at each user pair (transmitter-receiver) is proposed in a (n, K)-user interference channel where K user pairs are allowed to simultaneously communicate with each other among n user pairs (K ≪ n). Each transmitter sends a single spatial stream and each user pair minimizes generating interference to the scheduled receivers and the received interference from the scheduled transmitters via transmit beamforming and receive beamforming, respectively. We analyze scaling of n to achieve K degrees-of-freedom (DoF) with high probability via the proposed beamforming technique. This results show that the proposed beamforming reduces the required network size (i.e., scaling of n) compared to the previous results on (n, K)-user interference channel.

Recently, the use of artificial noise has attracted considerable attention in enhancing the physical-layer security of wireless systems. However, the interaction between artificially generated noise and the inherent network interference can significantly affect the level of secrecy. In this paper, we consider the additional secrecy enhancement with artificial noise and secrecy protected zone in the presence of eavesdroppers and interferers with unknown locations. Specifically, we derive the secrecy transmission rate and investigate the relationship between artificial noise and various system parameters like secrecy protected zone radius and intensity of interferers and eavesdroppers on the secrecy transmission rate. In interference-limited networks, we derive the optimal power allocation between the information-bearing signal and artificial noise to maximize the achievable secrecy transmission rate subject to connection and secrecy outage probabilities. Numerical results show that artificial noise is still beneficial in the presence of inherent network interference to improve secrecy transmission rate and provide rules of thumb to quantify when optimal power allocation is useful.

In this paper, we study the achievable degree-of-freedom (DoF) of an (n, K)-user interference network where n transmitter-receiver pairs are randomly distributed but only K transmitter-receiver pairs are allowed to communicate (n ≫ K). We propose a distributed user scheduling method to achieve the maximum DoF (i.e., K), which sequentially adds a transmitter-receiver pair causing/receiving interference to/from the previously selected transmitter-receiver pairs below a certain threshold level. It is proven that the maximum K DoF is achievable if the total number of communication pairs n scales ω(SNRK(K-1)) where SNR denotes the received signal-to-noise ratio. In addition, the total amount of the required feedback for the worst case and the feedback overhead per user are investigated in interference limited environments.

We investigate achievable degrees-of-freedom (DoF) of an (N, K)-user interference channel where only K user (transmitter-receiver) pairs among N user pairs are allowed to simultaneously communicate in a dense network (N ≫ K). Each node is assumed to have M antennas and to be randomly located. We propose a distributed scheduling protocol to achieve the maximum DoF (i.e., MK), which sequentially and opportunistically selects a user pair causing/receiving interference lower than a pre-determined threshold to/from already selected user pairs in each step. It is proven that the proposed protocol achieves the maximum DoF, MK, in the (N, K)-user interference channel with less stringent network size N, compared with the conventional centralized protocol which has been known as the best. With zero-forcing detector at receiver, we prove that it is sufficient that the network size N scales at least as ω(SNR(M2)K(K-1))to achieve the maximum number of DoF MK, where SNR denotes the received signal-to-noise ratio. We also investigate the required feedback overheads of the proposed protocol and show that it is quite small when the network is strongly interference-limited because only a small number of users are required to transmit their signaling. Our numerical results show that our proposed scheme controls interference more effectively than the centralized protocol.

In this paper, we propose two opportunistic jammer selection schemes for secure communications aided by jammers using the concept of interference alignment. Because jamming signals are interference to both a legitimate receiver and a eavesdropper, the legitimate receiver selects two jammers whose jamming signals are the most aligned in a small dimensional subspace. The alignment is measured by either interference-to-noise ratio (INR) or chordal distance for the opportunistic jammer selection. We find the achievable secure degrees of freedom (DoF) by the proposed jammer selection schemes when the number of jammers goes to infinity and find the computational complexity of each scheme.