This paper presents indoor and outdoor experimental results on 4-by-8 single-user (SU)-multiple-input multiple-output (MIMO) multiplexing based on 730.5 MHz bandwidth transmission when applying carrier aggregation (CA) with 8 component carriers (CCs) in a 15 GHz frequency band in the downlink of 5G cellular radio access. Beam tracking with massive MIMO is implemented in a 5G testbed to support user mobility with a narrow beam. In addition, channel state information (CSI) acquisition functionality is implemented for the scheduler to select appropriate beams. Experimental results in an indoor multi-path rich environment show the gain up to 34 % with CSI acquisition compared to the case of without CSI acquisition in a line-of-sight (LoS) environment with high rank MIMO transmission. The results also show the gain up to 55 % with CSI acquisition compared to the case of without CSI acquisition in LoS conditions due to reflections by buildings.

We consider a Gaussian relay network, which has to protect the message from a powerful eavesdropper, which has the possibility of listening to the transmitted signals on orthogonal channels. The secrecy capacity of the Gaussian network is approximated by considering the corresponding network in the deterministic discrete superposition model. Upper and lower bounds on the secrecy capacity are found in terms of the deterministic model, which are potentially easier to evaluate. We perform this evaluation for the particular topology of the parallel relay network, where the relays form a parallel layer between the source and the destination. By analyzing the deterministic model, we approximate the secrecy capacity within a constant gap. The approximation can be expressed just in terms of the channel gains of the network. It is therefore possible to deduct that the simple scheme of hiding the transmitted signals in noise is approximately optimal.

This paper investigates cooperation for secrecy in cognitive radio networks. In particular, we consider a four-node cognitive scenario where the secondary receiver is treated as a potential eavesdropper with respect to the primary transmission. The cognitive transmitter can help the primary transmission, and it should also ensure that the primary message is not leaked to the secondary user. We consider two cognitive scenarios depending on whether the secondary transmitter knows the primary message or not. In the first case, the secondary transmitter is unaware of the primary transmitter's message and acts as a helping interferer to enhance the secrecy of the primary transmission, whereas in the second case, relaying of the primary message is also within its capabilities. First, we find achievable rate regions for these two scenarios in the case of AWGN channels. We then investigate three different optimization problems: the maximization of the primary rate, the maximization of the secondary rate and the minimization of the secondary transmit power. For these optimization problems, we find closed-form expressions in important special cases. Furthermore, we analyze the cooperation between the primary and secondary transmitters from a game-theoretic perspective. We model their interaction as a Stackelberg game, for which we define and find the Stackelberg equilibrium. Finally, we use numerical examples to illustrate the rate regions, the three optimizations, and the impact of the Stackelberg game on the achievable rates and on the transmission strategies of the secondary transmitter.

This paper characterizes achievable rate regions for the Gaussian partially cognitive interference channel with multiple cognitive pairs (K-PCIFC), where the cognitive transmitters know one part of the primary transmitter's message. We explore a novel methodology using the deterministic discrete superposition model (DSM). We find codes and their achievable rate regions in the DSM, and we show that they yield achievable rate regions in the Gaussian model. Our coding scheme in the DSM can be applied in general scenarios. We devise an achievable rate region for the K-PCIFC, which is within a constant gap to known outer bounds for K = 2 in the weak interference regime. From our expressions we derive guidelines for designing the cognitive link between the primary transmitter and the cognitive transmitters. Furthermore, we show that the gain from cognition diminishes for increasing K.

This paper explores the trade-off between cooperation and secrecy in cognitive radio networks. We consider a scenario consisting of a primary and a secondary system. In the simplest case, each system is represented by a pair of transmitter and receiver. We assume a secrecy constraint on the transmission in the sense that the message of the primary transmitter has to be concealed from the secondary receiver. Both situations where the secondary transmitter is aware and unaware of the primary message are investigated and compared. In the first case, the secondary transmitter helps by allocating power for jamming, which increases the secrecy of the first message. In the latter case, it can also act as a relay for the primary message, thus improving the reliability of the primary transmission. Furthermore, we extend our results to the scenario where the secondary system comprises multiple receivers. For each case we present achievable rate regions. We then provide numerical illustrations for these rate regions. Our main result is that, in spite of the secrecy constraint, cooperation is beneficial in terms of the achievable rates. In particular, the secondary system can achieve a significant rate without decreasing the primary rate below the benchmark rate achievable without the help of the secondary transmitter. Finally, we investigate the influence of the distances between users on the system's performance.

In this paper we show how the recently proposed linear finite-field deterministic model (LFFM) can be used to design transmission strategies for the corresponding AWGN model of wireless relay networks. The transmission scheme in the AWGN model uses hierarchical modulation to transmit information on multiple layers. We show that a transmission strategy in the LFFM can be translated to the AWGN model if it is coordinated, that is, if the amount of interference is limited in a certain way. We consider two types of coordination, full and partial, with different restrictions on the transmission scheme. In both cases we show that the rate in the AWGN model is at most a constant gap below the rate in the LFFM, which provides a link between the models. Closed-form upper bounds on the gap are derived based on the analysis of noise and interference forwarding. The bounds are evaluated numerically, and the dependency on the system parameters and the parameters of coordination are discussed. The trade-off between full and partial coordination and the corresponding parameters are illustrated.

We approximate the capacity of the Gaussian parallel relay network with general channel gains. Our strategy is to find capacity approximations for the corresponding network in the discrete superposition model and to use the fact that those are an approximation for the Gaussian capacity. The gap between our approximation and the Gaussian capacity is a constant depending only on the number of relays, hence it is a valuable characterization for the regime of high SNR and high rate.

Recently, it has been shown that the capacity of certain Gaussian networks can be approximated by the capacity of the corresponding network in the discrete superposition model (DSM). The gap between the capacities is an additive constant only depending on the number of nodes in the network. Hence, the capacity in the DSM is a good approximation in the high SNR regime. Finding this capacity involves optimizing over a finite set of coding strategies. However, the problem space grows with both the number of nodes and with SNR, rendering the optimization infeasible. In this paper we find upper and lower bounds on the capacity in the DSM. We start with the point-to-point channel, and we extend our strategy to the multiple-access channel. We show that the gap between our bounds is at most an additive constant independent of the channel gains. Hence, combining our results with the results, we find closed form bounds on the Gaussian capacity to within an additive constant.

A constant gap between the deterministic model of a class of a wireless relay network and its Gaussian model counterpart is derived. The method is constructive in the sense that a transmission solution in the deterministic model that obeys certain constraints can directly be translated into a transmission in the Gaussian model. We show that the rate in the Gaussian model is at most a constant gap below the rate in the deterministic model, and we derive an upper bound on this gap.