Malcolm Egan

Secrecy Sum-Rates for Multi-User MIMO Regularized Channel Inversion Precoding

In this paper, we propose a linear precoder for the downlink of a multi-user MIMO system with multiple users that potentially act as eavesdroppers. The proposed precoder is based on regularized channel inversion (RCI) with a regularization parameter α and power allocation vector chosen in such a way that the achievable secrecy sum-rate is maximized. We consider the worst-case scenario for the multi-user MIMO system, where the transmitter assumes users cooperate to eavesdrop on other users. We derive the achievable secrecy sum-rate and obtain the closed-form expression for the optimal regularization parameter αLS of the precoder using large-system analysis. We show that the RCI precoder with αLS outperforms several other linear precoding schemes, and it achieves a secrecy sum-rate that has same scaling factor as the sum-rate achieved by the optimum RCI precoder without secrecy requirements. We propose a power allocation algorithm to maximize the secrecy sum-rate for fixed α. We then extend our algorithm to maximize the secrecy sum-rate by jointly optimizing α and the power allocation vector. The jointly optimized precoder outperforms RCI with αLS and equal power allocation by up to 20 percent at practical values of the signal-to-noise ratio and for 4 users and 4 transmit antennas.

Variance-constrained capacity of the molecular timing channel with synchronization error

Molecular communication is set to play an important role in the design of complex biological and chemical systems. An important class of molecular communication systems is based on the timing channel, where information is encoded in the delay of the transmitted molecule - a synchronous approach. At present, a widely used modeling assumption is the perfect synchronization between the transmitter and the receiver. Unfortunately, this assumption is unlikely to hold in most practical molecular systems. To remedy this, we introduce a clock into the model - leading to the molecular timing channel with synchronization error. To quantify the behavior of this new system, we derive upper and lower bounds on the variance-constrained capacity, which we view as the step between the mean-delay and the peak-delay constrained capacity. By numerically evaluating our bounds, we obtain a key practical insight: the drift velocity of the clock links does not need to be significantly larger than the drift velocity of the information link, in order to achieve the variance-constrained capacity with perfect synchronization.

A New Cross-Layer User Scheduler for Wireless Multimedia Relay Networks

We propose a new scheduler for wireless multimedia relay networks (WMRNs). Our scheduler is designed to account for delay, symbol error probability (SEP), and packet loss probability (PLP) due to buffer overflow. We develop a cross-layer scheduling approach for the downlink to balance these system metrics. Our scheduler is based on a new metric which is referred to as the delay in packet scheduling (DPS). The user with the largest weighted signal-to-noise ratio is scheduled, where the weight is a function of the DPS. We then derive analytical expressions for the probability mass function (PMF) of the DPS, and the SEP of the scheduled user in Rayleigh fading. We derive an analytical approximation for the PMF of the buffer state. An analytical expression is then derived for the PLP due to buffer overflow. Our analysis is verified via simulations. We show the probability that a target DPS is met is 30% higher for our new scheme compared to the standard opportunistic equal weight scheduler, with negligible degradation in the SEP of the scheduled user. This can lead to a 85% improvement in the PLP.

Performance of Wireless Nano-Sensor Networks with Energy Harvesting

With recent advances in energy harvesting technology, practical wireless nano-sensor networks (WNSNs) are coming within reach. An important aspect of these WNSNs is that the charge time is significantly longer than each sensor mote can reliably transmit its data-leading to sparse transmission requests in the time-domain. In this paper, we propose a compressed sensing-based approach for efficient request handling. We show that our scheme can achieve near contention free transmission while ensuring that each sensor motes queue is stable. This sharply contrasts with the unstable sensor mote queues obtained using the standard round- robin approach. To guide design, we also derive closed-form expressions for the average energy consumption, which show that the average energy state of the battery increases exponentially with the transmit power.

Structured and Sparse Limited Feedback Codebooks for Multiuser MIMO

A key component of multiuser MIMO using zero-forcing precoding is the feedback of quantized channel state information to the base station. A problem arises when each user has a common codebook as the quantized channels can form a singular matrix that results in a reduced sum-rate. In this paper, we propose two new structured constructions to generate different codebooks at each user via transformations of a base codebook. The first construction is based on the Householder transform, which is used to construct a different codebook at each user for most types of base codebooks, with no storage in addition to the base codebook. A feature of our first construction is that the transformed codebook using the Fourier base codebook has a search complexity reduction of up to 50% compared to the standard approach, although only one additional unique codebook can be constructed with this type of base codebook. To construct multiple different codebooks using the Fourier base codebook, we propose a second construction that is based on the representation theory of groups. We show that both our constructions significantly reduce storage requirements compared with the intuitive but impractical random construction, while obtaining the same sum-rate performance. In particular, we only require elements generated directly from the base codebook or from finite fields, instead of random complex numbers.

A Coordinated Multipoint Scheduler for Packet Loss Reduction

Coordinated multipoint (CoMP) is a base station (BS) cooperation technique to boost the signal-to-noise ratio (SNR) of cell-edge users in future generation wireless networks. We propose a fixed weight CoMP downlink scheduler to reduce the packet loss probability (PLP) due to buffer overflow in BSs with finite queues. The CoMP scheduler selects a single BS to serve the associated cell-edge user with the largest weighted SNR. To meet PLP targets, we develop a simple strategy to design the packet transmission time and the scheduling weights of each BS. The network design capitalizes on our new closed-form expression for the PLP that relates three key network parameters: packet arrival rate, packet transmission time, and probability that each BS is scheduled. We compare the proposed fixed weight scheduler with an adaptive weight scheduler that requires instantaneous packet delay information. We show via analysis and simulation that the fixed weight scheduler can achieve a comparable PLP to the adaptive weight scheduler, while reducing communication overheads for the BSs.

Codebook Design for the Finite Rate MIMO Broadcast Channel with Zero-Forcing Precoding

We present a novel codebook design criterion for the limited feedback MIMO broadcast channel with zero-forcing precoding. To reduce system implementation complexity, each user has the same codebook. We derive a new sum-rate bound, show the bound maximization problem is invex and explicitly solve it using the Karush-Kuhn-Tucker (KKT) conditions. We show that the solution has the same structure as Grassmannian frames. We also derive a new lower bound on the outage probability. We show via simulations that our codebooks designed using Grassmannian frames outperform random vector quantization with different codebooks at each user for codebook sizes greater than

Wireless vehicular networks in emergencies: A single frequency network approach

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Event Detection in Molecular Communication Networks With Anomalous Diffusion

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A Double Auction Mechanism for On-Demand Transport Networks

Obtaining high quality sensor information is critical in vehicular emergencies. However, existing standards such as IEEE 802.11p/DSRC and LTE-A cannot support either the required data rates or the latency requirements. One solution to this problem is for municipalities to invest in dedicated base stations to ensure that drivers have the information they need to make safe decisions in or near accidents. In this paper we further propose that these municipality-owned base stations form a Single Frequency Network (SFN). In order to ensure that transmissions are reliable, we derive tight bounds on the outage probability when the SFN is overlaid on an existing cellular network. Using our bounds, we propose a transmission power allocation algorithm. We show that our power allocation model can reduce the total instantaneous SFN transmission power up to 20 times compared to a static uniform power allocation solution, for the considered scenarios. The result is particularly important when base stations rely on an off-grid power source (i.e., batteries).