arXiv subjects

Mai Vu

Publications and source records attributed to Mai Vu.

45 records · Page 3Linked to original sources

arXiv2011

Decode-forward and Compute-forward Coding Schemes for the Two-Way Relay Channel

We consider the full-duplex two-way relay channel with direct link between two users and propose two coding schemes: a partial decode-forward scheme, and a combined decode-forward and compute-forward scheme. Both schemes use rate-splitting and superposition coding at each user and generate codewords for each node independently. When applied to the Gaussian channel, partial decode-forward can strictly increase the rate region over decode-forward, which is opposite to the one-way relay channel. The combined scheme uses superposition coding of both Gaussian and lattice codes to allow the relay to decode the Gaussian parts and compute the lattice parts. This scheme can also achieve new rates and outperform both decode-forward and compute-forward separately. These schemes are steps towards understanding the optimal coding.

cs.IT↗

arXiv2011

Achievable Rates and Outer Bound for the Half-Duplex MAC with Generalized Feedback

This paper provides comprehensive coding and outer bound for the half-duplex multiple access channel with generalized feedback (MAC-GF). Two users communicate with one destination over a discrete memoryless channel using time division. Each transmission block is divided into 3 time slots with variable durations: the destination is always in receive mode, while each user alternatively transmits and receives during the first 2 time slots, then both cooperate to send information during the last one. The paper proposes two decode-forward based coding schemes, analyzes their rate regions, and also derives two outer bounds with rate constraints similar to the achievable regions. Both schemes requires no block Makovity, allowing the destination to decode at the end of each block without any delay. In the first scheme, the codewords in the third time slot are superimposed on the codewords of the first two, whereas in the second scheme, these codewords are independent. While the second scheme is simpler, the first scheme helps emphasize the importance of joint decoding over separate decoding among multiple time slots at the destination. For the Gaussian channel, the two schemes with joint decoding are equivalent, as are the two outer bounds. For physically degraded Gaussian channels, the proposed schemes achieve the capacity. Extension to the m-user half-duplex MAC-GF are provided. Numerical results for the Gaussian channel shows significant rate region improvement over the classical MAC and that the outer bound becomes increasingly tight as the inter-user link quality increases

cs.IT↗

arXiv2011

The Capacity of MIMO Channels with Per-Antenna Power Constraint

We establish the optimal input signaling and the capacity of MIMO channels under per-antenna power constraint. While admitting a linear eigenbeam structure, the optimal input is no longer diagonalizable by the channel right singular vectors as with sum power constraint. We formulate the capacity optimization as an SDP problem and solve in closed-form the optimal input covariance as a function of the dual variable. We then design an efficient algorithm to find this optimal input signaling for all channel sizes. The proposed algorithm allows for straightforward implementation in practical systems in real time. Simulation results show that with equal constraint per antenna, capacity with per-antenna power can be close to capacity with sum power, but as the constraint becomes more skew, the two capacities diverge. Forcing input eigenbeams to match the channel right singular vectors achieves no improvement over independent signaling and can even be detrimental to capacity.

cs.IT↗

arXiv2011

A Half-Duplex Cooperative Scheme with Partial Decode-Forward Relaying

In this paper, we present a new cooperative communication scheme consisting of two users in half-duplex mode communicating with one destination over a discrete memoryless channel. The users encode messages in independent blocks and divide the transmission of each block into 3 time slots with variable durations. Cooperation is performed by partial decodeforward relaying over these 3 time slots. During the first two time slots, each user alternatively transmits and decodes, while during the last time slot, both users cooperate to send information to the destination. An achievable rate region for this scheme is derived using superposition encoding and joint maximum likelihood (ML) decoding across the 3 time slots. An example of the Gaussian channel is treated in detail and its achievable rate region is given explicitly. Results show that the proposed half-duplex scheme achieves significantly larger rate region than the classical multiple access channel and approaches the performance of a full-duplex cooperative scheme as the inter-user channel quality increases.

cs.IT↗

arXiv2011

Superposition Coding-Based Bounds and Capacity for the Cognitive Z-Interference Channels

This paper considers the cognitive interference channel (CIC) with two transmitters and two receivers, in which the cognitive transmitter non-causally knows the message and codeword of the primary transmitter. We first introduce a discrete memoryless more capable CIC, which is an extension to the more capable broadcast channel (BC). Using superposition coding, we propose an inner bound and an outer bound on its capacity region. The outer bound is also valid when the primary user is under strong interference. For the Gaussian CIC, this outer bound applies for $|a| \geq 1 $, where $a$ is the gain of interference link from secondary user to primary receiver. These capacity inner and outer bounds are then applied to the Gaussian cognitive Z-interference channel (GCZIC) where only the primary receiver suffers interference. Upon showing that jointly Gaussian input maximizes these bounds for the GCZIC, we evaluate the bounds for this channel. The new outer bound is strictly tighter than other outer bounds on the capacity of the GCZIC at strong interference ($a^2 \geq 1 $). Especially, the outer bound coincides with the inner bound for $|a| \geq \sqrt{1 + P_1}$ and thus, establishes the capacity of the GCZIC at this range. For such a large $a$, superposition encoding at the cognitive transmitter and successive decoding at the primary receiver are capacity-achieving.

cs.IT↗

arXiv2011

MISO Capacity with Per-Antenna Power Constraint

We establish in closed-form the capacity and the optimal signaling scheme for a MISO channel with per-antenna power constraint. Two cases of channel state information are considered: constant channel known at both the transmitter and receiver, and Rayleigh fading channel known only at the receiver. For the first case, the optimal signaling scheme is beamforming with the phases of the beam weights matched to the phases of the channel coefficients, but the amplitudes independent of the channel coefficients and dependent only on the constrained powers. For the second case, the optimal scheme is to send independent signals from the antennas with the constrained powers. In both cases, the capacity with per-antenna power constraint is usually less than that with sum power constraint.

cs.IT↗

arXiv2010

Gelfand-Pinsker coding achieves the interference-free capacity

For a discrete memoryless channel with non-causal state information available only at the encoder, it is well-known that Gelfand-Pinsker coding achieves its capacity. In this paper, we analyze Gelfand-Pinsker coding scheme and capacity to bring out further understandings. We show that Gelfand-Pinsker capacity is equal to the interference-free capacity. Thus the capacity of a channel with non-causal state information available only at the encoder is the same as if the state information is also available at the decoder. Furthermore, the capacity-achieving conditional input distributions in these two cases are the same. This lets us connect the studied channel with state to the multiple access channel (MAC) with correlated sources and show that under certain conditions, the receiver can decode both the message and the state information. This dual decoding can be obtained in particular if the state sequences come from a known codebook with rate satisfying a simple constraint. In such a case, we can modify Gelfand-Pinsker coding by pre-building multiple codebooks of input sequences $X^n$, each codebook is for a given state sequence $S^n$, upon generating the auxiliary $U^n$ sequences. The modified Gelfand-Pinsker coding scheme achieves the capacity of the MAC with degraded message set and still allows for decoding of just the message at any state information rate. We then revisit dirty-paper coding for the Gaussian channel to verify our analysis and modified coding scheme.

cs.IT↗

arXiv2009

Cognitive Networks Achieve Throughput Scaling of a Homogeneous Network

We study two distinct, but overlapping, networks that operate at the same time, space, and frequency. The first network consists of $n$ randomly distributed \emph{primary users}, which form either an ad hoc network, or an infrastructure-supported ad hoc network with $l$ additional base stations. The second network consists of $m$ randomly distributed, ad hoc secondary users or cognitive users. The primary users have priority access to the spectrum and do not need to change their communication protocol in the presence of secondary users. The secondary users, however, need to adjust their protocol based on knowledge about the locations of the primary nodes to bring little loss to the primary network's throughput. By introducing preservation regions around primary receivers and avoidance regions around primary base stations, we propose two modified multihop routing protocols for the cognitive users. Base on percolation theory, we show that when the secondary network is denser than the primary network, both networks can simultaneously achieve the same throughput scaling law as a stand-alone network. Furthermore, the primary network throughput is subject to only a vanishingly fractional loss. Specifically, for the ad hoc and the infrastructure-supported primary models, the primary network achieves sum throughputs of order $n^{1/2}$ and $\max\{n^{1/2},l\}$, respectively. For both primary network models, for any $δ>0$, the secondary network can achieve sum throughput of order $m^{1/2-δ}$ with an arbitrarily small fraction of outage. Thus, almost all secondary source-destination pairs can communicate at a rate of order $m^{-1/2-δ}$.

cs.IT↗

arXiv2007

Scaling Laws of Cognitive Networks

We consider a cognitive network consisting of n random pairs of cognitive transmitters and receivers communicating simultaneously in the presence of multiple primary users. Of interest is how the maximum throughput achieved by the cognitive users scales with n. Furthermore, how far these users must be from a primary user to guarantee a given primary outage. Two scenarios are considered for the network scaling law: (i) when each cognitive transmitter uses constant power to communicate with a cognitive receiver at a bounded distance away, and (ii) when each cognitive transmitter scales its power according to the distance to a considered primary user, allowing the cognitive transmitter-receiver distances to grow. Using single-hop transmission, suitable for cognitive devices of opportunistic nature, we show that, in both scenarios, with path loss larger than 2, the cognitive network throughput scales linearly with the number of cognitive users. We then explore the radius of a primary exclusive region void of cognitive transmitters. We obtain bounds on this radius for a given primary outage constraint. These bounds can help in the design of a primary network with exclusive regions, outside of which cognitive users may transmit freely. Our results show that opportunistic secondary spectrum access using single-hop transmission is promising.

cs.IT↗