This paper investigates price-based resource allocation strategies for two-tier femtocell networks, in which a central macrocell is underlaid with distributed femtocells, all operating over the same ...frequency band. Assuming that the macrocell base station (MBS) protects itself by pricing the interference from femtocell users, a Stackelberg game is formulated to study the joint utility maximization of the macrocell and femtocells subject to a maximum tolerable interference power constraint at the MBS. Two practical femtocell network models are investigated: sparsely deployed scenario for rural areas and densely deployed scenario for urban areas. For each scenario, two pricing schemes: uniform pricing and non-uniform pricing, are proposed. The Stackelberg equilibriums for the proposed games are characterized, and an effective distributed interference price bargaining algorithm with guaranteed convergence is proposed for the uniform-pricing case. Numerical examples are presented to verify the proposed studies. It is shown that the proposed schemes are effective in resource allocation and macrocell protection for both the uplink and downlink transmissions in spectrum-sharing femtocell networks.
The difficulty of modeling energy consumption in communication systems leads to challenges in energy harvesting (EH) systems, in which nodes scavenge energy from their environment. An EH receiver ...must harvest enough energy for demodulating and decoding. The energy required depends upon factors, such as code rate and signal-to-noise ratio, which can be adjusted dynamically. We consider a receiver which harvests energy from the transmitter and other ambient sources, meaning the received signal is used for both EH and information decoding. Assuming a generalized function for energy consumption, we maximize the total number of information bits decoded, under both average and peak power constraints at the transmitter, by carefully optimizing the power used for EH, power used for information transmission, fraction of time for EH, and code rate. For transmission over a single block, we find there exist problem parameters for which either maximizing power for information transmission or maximizing power for EH is optimal. In the general case, the optimal solution is a tradeoff of the two. For transmission over multiple blocks, we give an upper bound on performance and give sufficient and necessary conditions to achieve this bound. Finally, we give some numerical results to illustrate our results and analysis.
In this paper, we revisit the discrete lossy Gray-Wyner problem. In particular, we derive its optimal second-order coding rate region, its error exponent (reliability function), and its moderate ...deviations constant under mild conditions on the source. To obtain the second-order asymptotics, we extend some ideas from Watanabe's work. In particular, we leverage the properties of an appropriate generalization of the conditional distortion-tilted information density, which was first introduced by Kostina and Verdú. The converse part uses a perturbation argument by Gu and Effros in their strong converse proof of the discrete Gray-Wyner problem. The achievability part uses two novel elements: 1) a generalization of various type covering lemmas and 2) the uniform continuity of the conditional rate-distortion function in both the source (joint) distribution and the distortion level. To obtain the error exponent, for the achievability part, we use the same generalized type covering lemma, and for the converse, we use the strong converse together with a change-of-measure technique. Finally, to obtain the moderate deviations constant, we apply the moderate deviations theorem to probabilities defined in terms of information spectrum quantities.
Energy harvesting (EH) relay communication systems with decoding energy costs in multiple block cases have not been widely studied. This paper investigates the relay network with a decode-and-forward ...relay powered by EH. Unlike other works, we consider the relay with energy decoding costs which harvests random energy from both a dedicated transmitter and other ambient radio-frequency (RF) sources. The EH relay adopts a harvest-receive-forward time-switching architecture. We optimize the time fractions of the three phases and the reception rate at the relay to maximize the offline throughput for single and multiple block cases under two EH scenarios. The multi-block optimization problem constitutes a complex non-convex problem, which we decouple into a single block problem with two auxiliary variables determined by an outer optimization problem. The original problem is finally solved at the cost of linear optimization after series of tricks. Several conclusions are derived: (i) energy storage is necessary (unnecessary) when the relay harvests energy from the transmitter (ambient RF sources), (ii) the optimal reception rate remains unchanged, while the optimal time fractions vary with the energy harvested from ambient RF sources leading to different average throughput. We give numerical simulations to verify our theoretical analysis.
Lens antenna arrays have become attractive for mmWave MIMO systems due to their energy-focusing and path-division properties. However, when the signals cannot be well differentiated at different ...array elements due to their similar incident angles, we cannot estimate their DoAs separately. In this paper, we present a DoA estimation algorithm for this situation. Our algorithm has three main steps: a special version of root multiple signal classification (MUSIC) for lens antenna arrays, outlier detection, and clustering. Numerical results show that our algorithm can achieve good performance even with a large number of signal sources, a large number of array elements, and a small number of snapshots.
In this paper, we consider medium access control (MAC) protocol design for random-access cognitive radio (CR) networks. A two-level opportunistic spectrum access strategy is proposed to optimize the ...system performance of the secondary network and to adequately protect the operation of the primary network. At the first level, secondary users (SUs) maintain a sufficient detection probability to avoid interference with primary users (PUs), and the spectrum sensing time is optimized to control the total traffic rate of the secondary network allowed for random access when the channel is detected to be available. At the second level, two MAC protocols called the slotted cognitive radio ALOHA (CR-ALOHA) and cognitive-radio-based carrier-sensing multiple access (CR-CSMA) are developed to deal with the packet scheduling of the secondary network. We employ normalized throughput and average packet delay as the network metrics and derive closed-form expressions to evaluate the performance of the secondary network for our proposed protocols. Moreover, we use the interference and agility factors as the performance parameters to measure the protection effects on the primary network. For various frame lengths and numbers of SUs, the optimal performance of throughput and delay can be achieved at the same spectrum sensing time, and there also exists a tradeoff between the achievable performance of the secondary network and the effects of protection on the primary network. Simulation results show that the CR-CSMA protocol outperforms the slotted CR-ALOHA protocol and that the PUs' activities have an influence on the performance of SUs for both the slotted CR-ALOHA and CR-CSMA.
In this paper, we consider the cooperative spectrum sensing problem for a cognitive radio (CR) mesh network, where secondary users (SUs) are allowed to share the spectrum band which is originally ...allocated to a primary users' (PUs) network. We propose two new cooperative spectrum sensing strategies, called amplify-and-relay (AR) and detect-and-relay (DR), aiming at improving the detection performance with the help of other eligible SUs so as to agilely vacate the channel to the primary network when the neighboring PUs switch to active state. AR and DR strategies are periodically executed during the spectrum sensing phase which is arranged at the beginning of each MAC frame. Based on AR and DR strategies, we derive the closed-form expressions of false alarm probability and detection probability for both single-relay and multi-relay models, with or without channel state information (CSI). Simulation results show that our proposed strategies achieve better performance than a non-cooperative (or non-relay) spectrum sensing method and an existing cooperative detection method. As expected, we observe that the detection performance improves as the number of eligible relay SUs increases, and furthermore, it is better for the known-CSI case than that of the unknown-CSI case.
In this paper, we revisit two multi-terminal lossy source coding problems: the lossy source coding problem with side information available at the encoder and one of the two decoders, which we term as ...the Kaspi problem (Kaspi, 1994), and the multiple description coding problem with one semi-deterministic distortion measure, which we refer to as the Fu-Yeung problem (Fu and Yeung, 2002). For the Kaspi problem, we first present the properties of optimal test channels. Subsequently, we generalize the notion of the distortion-tilted information density for the lossy source coding problem to the Kaspi problem and prove a non-asymptotic converse bound using the properties of optimal test channels and the well-defined distortion-tilted information density. Finally, for discrete memoryless sources, we derive refined asymptotics which includes the second-order, large, and moderate deviations asymptotics. In the converse proof of second-order asymptotics, we apply the Berry-Esseen theorem to the derived non-asymptotic converse bound. The achievability proof follows by first proving a type-covering lemma tailored to the Kaspi problem, then properly Taylor expanding the well-defined distortion-tilted information densities and finally applying the Berry-Esseen theorem. We then generalize the methods used in the Kaspi problem to the Fu-Yeung problem. As a result, we obtain the properties of optimal test channels for the minimum sum-rate function, a non-asymptotic converse bound and refined asymptotics for discrete memoryless sources. Since the successive refinement problem is a special case of the Fu-Yeung problem, as a by-product, we obtain a non-asymptotic converse bound for the successive refinement problem, which is a strict generalization of the non-asymptotic converse bound for successively refinable sources (Zhou, Tan, and Motani, 2017).
Estimating power system states accurately is crucial to the reliable operation of power grids. Traditional weighted least square (WLS) state estimation methods face the rising threat of ...cyber-attacks, such as false data injection attacks, which can pass the bad data detection process in WLS state estimation. In this paper, we propose a new detection method to detect false data injection attacks by tracking the dynamics of measurement variations. The Kullback-Leibler distance (KLD) is used to calculate the distance between two probability distributions derived from measurement variations. When false data are injected into the power systems, the probability distributions of the measurement variations will deviate from the historical data, thus leading to a larger KLD. The proposed method is tested on IEEE 14 bus system using load data from the New York independent system operator with different attack scenarios. We have also tested our method on false data injection attacks that replace current measurement data with historical measurement data. Test results show that the proposed approach can accurately detect most of the attacks.
In emerging fifth generation and beyond wireless communication systems, communication nodes are expected to support information flows that are freshness-sensitive , along with broadband traffic ...having high data rate requirements. Freshness-sensitive flows, where freshness is quantified by a metric called the age of information (AoI), are naturally assigned priority over resources. Motivated by this, we consider long-term average throughput maximization in a single user fading channel, subject to constraints on average AoI and power, and knowledge of channel state information at the transmitter (CSIT), which is the realization of channel power gains. We consider two scenarios: (i) when Perfect CSIT is available and (ii) when CSIT is not available. In both scenarios, the channel distribution information is available. We consider a generate-at-will model, in which update packets can be generated in any block of interest, at the transmitter. We propose simple age-independent stationary randomized policies (AI-SRP), which allocate powers at the transmitter based only on the channel state and/or distribution information, without any knowledge of the AoI. We show that the optimal long-term average throughputs achieved by the AI-SRPs are equal to at least half of the throughputs achieved by optimal policies, independent of all the parameters of the problem. Furthermore, we provide an expression that bounds the difference in throughputs achieved by the optimal policies and AI-SRPs. Finally, we provide extensive numerical results to illustrate the performance of AI-SRPs.
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