Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userUsing Continuous Power Modulation for Exchanging Local Channel State Information
162
0
0.0
(
0
)
Added by
Chao Zhang
Publication date
2017
fields
Informatics Engineering
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
This letter provides a simple but efficient technique, which allows each transmitter of an interference network, to exchange local channel state information with the other transmitters. One salient feature of the proposed technique is that a transmitter only needs measurements of the signal power at its intended receiver to implement it, making direct inter-transmitter signaling channels unnecessary. The key idea to achieve this is to use a transient period during which the continuous power level of a transmitter is taken to be the linear combination of the channel gains to be exchanged.
rate research
Read More
We consider the problem where a group of n nodes, connected to the same broadcast channel (e.g., a wireless network), want to generate a common secret bitstream, in the presence of an adversary Eve, who tries to obtain information on the bitstream. We assume that the nodes initially share a (small) piece of information, but do not have access to any out-of-band channel. We ask the question: can this problem be solved without relying on Eves computational limitations, i.e., without using any form of public-key cryptography? We propose a secret-agreement protocol, where the n nodes of the group keep exchanging bits until they have all agreed on a bit sequence that Eve cannot reconstruct with very high probability. In this task, the nodes are assisted by a small number of interferers, whose role is to create channel noise in a way that bounds the amount of information Eve can overhear. Our protocol has polynomial-time complexity and requires no changes to the physical or MAC layer of network devices. First, we formally show that, under standard theoretical assumptions, our protocol is information-theoretically secure, achieves optimal secret-generation rate for n = 2 nodes, and scales well to an arbitrary number of nodes. Second, we adapt our protocol to a small wireless 14-square-meter testbed; we experimentally show that, if Eve uses a standard wireless physical layer and is not too close to any of the nodes, 8 nodes can achieve a secret-generation rate of 38 Kbps. To the best of our knowledge, ours is the first experimental demonstration of information-theoretic secret exchange on a wireless network at a rate beyond a few tens of bits per second.
In this work, we combine the two notions of timely delivery of information in order to study their interplay; namely, deadline-constrained packet delivery due to latency constraints and freshness of information at the destination. More specifically, we consider a two-user multiple access setup with random access, in which user 1 is a wireless device with a queue and has external bursty traffic which is deadline-constrained, while user 2 monitors a sensor and transmits status updates to the destination. For this simple, yet meaningful setup, we provide analytical expressions for the throughput and drop probability of user 1, and an analytical expression for the average Age of Information (AoI) of user 2 monitoring the sensor. The relations reveal that there is a trade-off between the average AoI of user 2 and the drop rate of user 1: the lower the average AoI, the higher the drop rate, and vice versa. Simulations corroborate the validity of our theoretical results.
In this paper, we present three new signal designs for Enhanced Spatial Modulation (ESM), which was recently introduced by the present authors. The basic idea of ESM is to convey information bits not only by the index(es) of the active transmit antenna(s) as in conventional Spatial Modulation (SM), but also by the types of the signal constellations used. The original ESM schemes were designed with reference to single-stream SM and involved one or more secondary modulations in addition to the primary modulation. Compared to single-stream SM, they provided either higher throughput or improved signal-to-noise ratio (SNR). In the present paper, we focus on multi-stream SM (MSM) and present three new ESM designs leading to increasing SNR gains when they are operated at the same spectral efficiency. The secondary signal constellations used in the first two designs are based on a single geometric interpolation step in the signal constellation plane, while the third design also makes use of additional constellations derived through a second interpolation step. The new ESM signal designs are described for MIMO systems with four transmit antennas two of which are active, but we also briefly present extensions to higher numbers of antennas. Theoretical analysis and simulation results indicate that the proposed designs provide a significant SNR gain over MSM.
In massive multiple-input multiple-output (MIMO) systems, acquisition of the channel state information at the transmitter side (CSIT) is crucial. In this paper, a practical CSIT estimation scheme is proposed for frequency division duplexing (FDD) massive MIMO systems. Specifically, each received pilot symbol is first quantized to one bit per dimension at the receiver side and then the quantized bits are fed back to the transmitter. A joint one-bit compressed sensing algorithm is implemented at the transmitter to recover the channel matrices. The algorithm leverages the hidden joint sparsity structure in the user channel matrices to minimize the training and feedback overhead, which is considered to be a major challenge for FDD systems. Moreover, the one-bit compressed sensing algorithm accurately recovers the channel directions for beamforming. The one-bit feedback mechanism can be implemented in practical systems using the uplink control channel. Simulation results show that the proposed scheme nearly achieves the maximum output signal-to-noise-ratio for beamforming based on the estimated CSIT.
Future wireless networks will be characterized by heterogeneous traffic requirements. Such requirements can be low-latency or minimum-throughput. Therefore, the network has to adjust to different needs. Usually, users with low-latency requirements have to deliver their demand within a specific time frame, i.e., before a deadline, and they co-exist with throughput oriented users. In addition, the users are mobile and they share the same wireless channel. Therefore, they have to adjust their power transmission to achieve reliable communication. However, due to the limited power budget of wireless mobile devices, a power-efficient scheduling scheme is required by the network. In this work, we cast a stochastic network optimization problem for minimizing the packet drop rate while guaranteeing a minimum throughput and taking into account the limited-power capabilities of the users. We apply tools from Lyapunov optimization theory in order to provide an algorithm, named Dynamic Power Control (DPC) algorithm, that solves the formulated problem in realtime. It is proved that the DPC algorithm gives a solution arbitrarily close to the optimal one. Simulation results show that our algorithm outperforms the baseline Largest-Debt-First (LDF) algorithm for short deadlines and multiple users.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
