Steven W. Boyd

Spectrum Monitoring During Reception in Dynamic Spectrum Access Cognitive Radio Networks

If a frequency band has primary and secondary users, then the cognitive radios of the secondary users must monitor the band and be prepared to cease their transmissions if a primary users radio begins to transmit. Traditional spectrum sensing requires the secondary radios to refrain from communicating while they check for the emergence of primary signals. We propose and evaluate methods by which the secondary radios can continue their communications while simultaneously monitoring the band to detect any transmissions that are initiated by the primary radios. Our methods for spectrum monitoring supplement traditional spectrum sensing and improve the communications efficiency of the secondary radios.

A soft-decision scaling metric employing receiver statistics for direct-sequence spread-spectrum packet radio networks

Packet radios for tactical networks must be able to communicate over highly dynamic links that are susceptible to variations in propagation loss, jamming, and multiple-access interference. We describe and evaluate an adaptive scaling metric for soft-decision decoding in direct-sequence spread-spectrum receivers for tactical radio networks. The metric is derived from post-detection signal quality statistics that are developed in the demodulator, and it is applied to the demodulatorpsilas soft-decision outputs before they are sent to the decoder. To maintain efficient use of assigned channel and spectrum resources, our metric exploits the nature of the spread-spectrum signal to obtain demodulator statistics during the reception of the desired transmission and therefore requires no pilot symbols or channel measurements. We compare the performance of our proposed adaptive scaling metric with a fixed soft-decision metric and with the log-likelihood ratio metric.

Enhanced SNR estimates from direct-sequence spread-spectrum demodulator statistics

Demodulator statistics are used in a binary direct-sequence spread-spectrum receiver to improve the performance of a well-known signal-to-noise ratio (SNR) estimate for ratios of the binary symbol energy to one-sided noise density that are below approximately 7 dB. The new estimate requires no pilot symbols, training sequences, data symbol decisions, or channel measurements, and it can be obtained prior to decoding.

Enhanced spectrum sensing techniques for dynamic spectrum access cognitive radio networks

Spectrum access protocols permit secondary users to utilize frequency bands when the bands are not in use by the primary owners. To determine if a frequency band is in use, spectrum sensing techniques (e.g., energy detection, feature detection) are employed by the secondary radios. Such techniques require that the secondary radios cease transmitting in the band during spectrum sensing periods. We propose a technique whereby cognitive radios that are secondary users of a frequency band can monitor the band for the emergence of primary signals while communicating. This enhancement permits more efficient use of spectrum by the secondary network, which results in increased channel utilization.

Receiver Statistics for Spectrum Monitoring While Communicating

In many dynamic spectrum access networks, it is necessary for secondary users to monitor the frequency band in which they are communicating so that they can determine if the primary user has begun transmission. Traditional sensing methods require the transmitters of the secondary users to be silent while spectrum monitoring is performed. Statistics that are derived easily in a communications receiver have the potential to permit a level of spectrum monitoring while the receiver is demodulating and decoding a packet, so that it is not necessary to silence the secondary transmitters. The proposed techniques for spectrum monitoring can supplement existing methods and reduce the amount of time that secondary users must refrain from communicating.

Adaptive Coding and Modulation for Multicast Transmission in Packet Radio Networks

A low-complexity protocol is described and evaluated for adaptation of the modulation and coding for multicast transmission in half-duplex packet radio networks. The adaptive multicast transmission protocol is designed to compensate for changes in propagation conditions that occur from packet to packet during a session with one sender and multiple receivers. The protocol relies on simple receiver statistics to obtain the control information for adapting the modulation and coding, and it also provides scheduling to avoid collisions among acknowledgments from the receivers. The throughput provided by the protocol is compared with performance results for hypothetical ideal adaptive multicast transmission protocols that are given perfect channel state information. We illustrate the importance of adaptive modulation and channel coding in systems that employ fountain coding for packet erasure correction.

Initial power adjustment and link adaptation from direct-sequence spread-spectrum demodulator statistics

Statistics obtained during demodulation are used in a direct-sequence spread-spectrum packet radio network to govern the adjustment of transmitter power within the first few packets of a session. The statistics are also employed by an adaptive transmission protocol to select the modulation parameters and the rate of the error-control code for each packet. The power-adjustment protocol uses the statistics to ensure that the transmitter power level is high enough to satisfy the signal strength requirements at the receiver and low enough to prevent unnecessary interference to nearby radios. We describe a protocol for which modulation and coding parameters are adapted to achieve the most efficient combination for the given channel conditions. We evaluate the performance of each protocol for several channels. The protocols are not given any information about the type of channel or the channel parameters, yet they are able to use the demodulator statistics to efficiently set the initial power level and adapt transmissions throughout the session.

Adaptive Direct-Sequence Spread-Spectrum for Packet Radio Networks

Our protocol adapts the error-control code and spreading factor on the links of a direct-sequence (DS) spread-spectrum packet radio network. The radios employ half-duplex transmission, and they operate with fixed power and bandwidth. There are no base stations, access points, or other infrastructure, and the protocol requires no power measurements or channel estimates. We compare the protocol with hypothetical ideal protocols that have perfect channel state information and maximize the throughput for each packet transmission.

Demodulator Statistics for Enhanced Soft-Decision Decoding in CDMA Packet Radio Systems

Next generation packet radio networks will have far greater processing capabilities than current radio systems. We propose and evaluate decoding techniques that make use of such capabilities to increase the probability of successful decoding. We propose a metric derived from statistics collected during demodulation in a binary CDMA receiver. We investigate several methods to apply the proposed metric to the demodulators soft-decision outputs prior to decoding. Our soft-decision decoding techniques are designed to mitigate the effects of interference from other signals in the frequency band. We compare the performance of our proposed metric to the log-likelihood ratio (LLR) metric, which requires that the mean signal level and noise variance are known for each bit position. Rather than attempt to estimate these parameters directly, our metric uses demodulator statistics and thus does not require pilot symbols or training sequences typically required by an LLR-based metric.

Information-Theoretic Methods for the Design and Evaluation of Adaptive Protocols for Direct-Sequence Spread-Spectrum Transmissions

Adaptation of the code rate and spreading factor for direct-sequence spread-spectrum packet radio transmissions provides much higher throughput than if the code rate and spreading factor are fixed. A low-complexity protocol for packet-by-packet adaptation can be obtained if receiver statistics that are developed during the demodulation of a packet are used to choose the code rate and spreading factor for the next packet. The design and evaluation of the protocol typically requires extensive simulations, especially for modern packet radio receivers that employ iterative decoding. We show that analytical methods based on Shannon capacity results greatly simplify the design of the adaptive protocol and provide good estimates of its throughput performance.