Discrete Fourier transform (DFT) codebook-based solutions are well-established for limited feedback schemes in frequency division duplex (FDD) systems. In recent years, data-aided solutions have been shown to achieve higher performance, enabled by the adaptivity of the feedback scheme to the propagation environment of the base station (BS) cell. In particular, a versatile limited feedback scheme utilizing Gaussian mixture models (GMMs) was recently introduced. The scheme supports multi-user communications, exhibits low complexity, supports parallelization, and offers significant flexibility concerning various system parameters. Conceptually, a GMM captures environment knowledge and is subsequently transferred to the mobile terminals (MTs) for online inference of feedback information. Afterward, the BS designs precoders using either directional information or a generative modeling-based approach. A major shortcoming of recent works is that the assessed system performance is only evaluated through synthetic simulation data that is generally unable to fully characterize the features of real-world environments. It raises the question of how the GMM-based feedback scheme performs on real-world measurement data, especially compared to the well-established DFT-based solution. Our experiments reveal that the GMM-based feedback scheme tremendously improves the system performance measured in terms of sum-rate, allowing to deploy systems with fewer pilots or feedback bits.

3GPP has completed the standardization of 5G NR positioning in Release 16 (Rel-16) and Rel-17, and the Rel-18 study on expanded and improved positioning was finished in November, 2022. The standard solutions enable several positioning techniques in efforts to improve accuracy and power efficiency, and to decrease the latency. RAT-independent positioning techniques have also been standardized to support user equipment positioning via satellites and sensors. This article provides the latest progress on 3GPP 5G positioning including requirements, use cases, and the newly supported positioning techniques in Release-17 and Release-18. Finally, future challenges are discussed.

5G networks will support network slicing to address the diverging needs of 5G applications. In this paper, we lay out a system model and mathematical framework to analyze the impact of resource granularity of network slicing on service availability and densification. We establish closed form expressions for service/slice availability in two extremum points of system operation that correspond to very fine and very coarse resource allocation for slice instances. We call the system operation around these extremum points as micro-slicing and macro-slicing regimes, respectively. Our analysis indicates that micro-slicing can achieve multiple orders of magnitude difference in service availability against macro-slicing even with as few as two slice types. Our results also indicate that in the short run, macro-slicing with resource over-provisioning is a viable approach to support few slice types at carrier-grade availability, but this approach fails to scale to higher densities of slice types. Another crucial outcome of our analysis is that the relationship between the slice availability and resource granularity (of slice instances) is not monotonic due to a quantization effect. Thus, rather than adopting a gradual reduction in slice instance sizes, system architects should consider moving directly into the micro-slicing regime in order to support higher service densities in 5G cloud.

To further improve the spectrum efficiency of 5G massive MIMO networks, bi-directional training (BiT) was developed for TDD systems to maximize the downlink weighted sum rate. However, the previous work was limited to narrowband systems. In this paper, we extend BiT for 5G wideband systems. A global, centralized optimization problem is first formulated for a wideband system. The (sub-optimal) solution is then distributed across the base stations and user equipment (UE), resulting into a wideband BiT algorithm that iteratively adapts transmission and reception filters for each base station and each UE with only local information. The algorithm may be seen as a narrowband BiT operating on an optimal narrowband representation of a group of subcarriers each with a different channel, and the optimal narrowband representation maintains the first and second moments of all the channels. Simulation results are provided to evaluate the performance of the algorithm in a wideband system.

The fifth-generation (5G) wireless communication system is expected to provide increasing throughput with advanced transmitting and receiving techniques. This paper considers the problem of maximizing the downlink data rate in a multi-cell system by jointly designing transceiver filters, transmission ranks, and user associations. The base stations (BSs) are equipped with massive multiple-input multiple-output (MIMO) antennas, and can cooperatively serve the user equipments (UEs) in the network. A global optimization problem is formulated to maximize the downlink weighted sum rate (WSR). We first propose a centralized solution by assuming the existence of a central controller and global channel state information (CSI). We use the re-weighted l1 method to approximate the problem, and then solve it using the fractional programming (FP) algorithm. Since the centralized algorithm only requires local channel and signal information, we decompose it and propose a distributed algorithm based on the idea of bi-directional training (BIT). By iterative uplink and downlink training, the precoders, receivers, and transmission ranks are adaptively optimized without explicit channel estimation. An uplink power control scheme is proposed to improve the fairness among the UEs. Simulation results are presented to evaluate the performance of proposed algorithms.

This paper investigates the performance of longitudinal control of a platoon of vehicles using communication of messages through a cellular network. We describe a platooning algorithm that utilizes, at each following vehicle, information communicated by the preceding vehicle and the lead vehicle of the platoon. The information received from the lead vehicle includes the position, speed and acceleration of the lead vehicle, whereas the information received from the preceding vehicle includes the target acceleration the preceding vehicle is attempting to achieve. The information is transmitted in messages that are received by a cellular base station, which then retransmits the messages to the intended vehicles. We perform an analysis of communication system capacity for a highway setting with dense configurations of platoons. We show that (a) the additional latency due to transmission through the infrastructure does not impact platooning performance, and (b) LTE can even support extreme vehicle densities with no impact to platooning.

With the ever-growing popularity of smartphones, new services are emerging where the local and positioning aspects becomes more important. Additionally, new types of traffic, such as vehicle-to-vehicle communications are being developed. In order to address these new trends, release-12 of LTE has started to evaluate, and possibly standardize, solutions for device-to-device (D2D) communication. This provides the foundations for the deployment of a D2D overlay. However, this should be viewed as a first step, and future LTE releases should encompass more advanced D2D communication techniques and architectures. In this paper, after reviewing the standardization progress for LTE in release-12, several possible improvements are examined for future releases both D2D discovery and communication. It is shown that the future D2D architecture should exploit the network when possible in order to provide an improved user experience and satisfy the need for more local services.

What will 5G be? What it will not be is an incremental advance on 4G. The previous four generations of cellular technology have each been a major paradigm shift that has broken backward compatibility. Indeed, 5G will need to be a paradigm shift that includes very high carrier frequencies with massive bandwidths, extreme base station and device densities, and unprecedented numbers of antennas. However, unlike the previous four generations, it will also be highly integrative: tying any new 5G air interface and spectrum together with LTE and WiFi to provide universal high-rate coverage and a seamless user experience. To support this, the core network will also have to reach unprecedented levels of flexibility and intelligence, spectrum regulation will need to be rethought and improved, and energy and cost efficiencies will become even more critical considerations. This paper discusses all of these topics, identifying key challenges for future research and preliminary 5G standardization activities, while providing a comprehensive overview of the current literature, and in particular of the papers appearing in this special issue.

ABSTRACT In this paper, a novel spectrum‐sensing scheme, called adaptive dual‐radio spectrum‐sensing scheme (ADRSS), is proposed for cognitive radio networks. In ADRSS, each secondary user (SU) is equipped with a dual radio. During the data transmission, with the received signal‐to‐noise ratio of primary user (PU) signal, the SU transmitter (SUT) and the SU receiver (SUR) are selected adaptively to sense one channel by one radio while communicating with each other by the other one. The sensing results of the SUR are sent to the SUT through feedback channels (e.g., ACK). After that, with the sensing results from the SUT or the SUR, the SUT can decide whether the channel switching should be carried out. The theoretical analysis and simulation results indicate that the normalized channel efficiency, defined as the expected ratio of time duration without interference to PUs in data transmission to the whole frame length, can be improved while satisfying the interference constraint to PUs. After that, an enhanced ADRSS is designed by integrating ADRSS with cooperative spectrum sensing, and the performance of ADRSS under imperfect feedback channel is also discussed. Copyright © 2011 John Wiley & Sons, Ltd.

In this paper, we investigate joint relay selection and power allocation to maximize system throughput with limited interference to licensed (primary) users in cognitive radio (CR) systems. As these two problems are coupled together, we first develop an optimal approach based on the dual method and then propose a suboptimal approach to reduce complexity while maintaining reasonable performance. From our simulation results, the proposed approaches can increase the system throughput by over 50%.

Cognitive radio (CR) networks are designed to utilize the licensed spectrum when it is not used by the primary (licensed) users. In this paper, we investigate how a CR user senses multiple channels and determine the optimal transmission duration and power allocation. When performing optimization, we take energy efficiency, throughput, and interference with the primary users into consideration and find a closed-form solution for transmission duration for chosen channels. It is shown that the proposed optimization approach significantly improves energy efficiency and throughput of CR networks.

In this paper, we investigate channel allocation for cooperative relays in cognitive radio networks. Different from conventional cooperative relay channels, cognitive radio relay channels are actually a combination of three kinds of channels: direct, dual-hop, and relay channels, which belong to different spectrum bands and provide parallel end-to-end transmission. In order to maximize the achievable end-to-end throughput, we propose two channel allocation approaches with different complexities to assign all the channels cooperatively. Numerical results illustrate the performance improvement in different number of available channels. In particular, it has about 40% improvement in throughput when the average SNR is 15 dB and eight available channels are used.

In this paper, we investigate bandwidth efficient combination of spectrum sensing information in cooperative cognitive radio (CR) networks. We propose a general approach in which CR users are allowed to simultaneously send local sensing data to a combining node through a common control channel, based on which we discuss bandwidth efficient combination schemes under two different cases. In the proposed schemes, the bandwidth required for reporting is fixed regardless of the number of cooperative users. With proper preprocessing at individual users, the proposed schemes maintain reasonable performance with the superposition of sensing data at the combining node. Simulation results also demonstrate the effectiveness of the proposed approach.

This letter proposes a probability-based scheme for combination of spectrum sensing information collected from cooperative cognitive radio users. The proposed scheme enables combination of both synchronous and asynchronous sensing information by utilizing the statistics of licensed band occupancy and is superior to conventional schemes in terms of detection performance.

Opportunistic spectrum access (OSA) in cognitive radio (CR) networks significantly improves spectrum efficiency by allowing secondary usage of licensed spectrum. In this paper, we propose a probabilistic resource allocation approach to further exploit the flexibility of OSA. Based on the probabilities of channel availability obtained from spectrum sensing, the proposed approach optimizes channel and power allocation in a multi-channel environment. The given algorithm maximizes the overall utility of a CR network and ensures sufficient protection of licensed users from unacceptable interference, which also supports diverse quality-of-service requirements and enables a distributed implementation in multi-user networks. Both analytical and simulation results demonstrate the effectiveness of this approach as well as its advantage over conventional approaches that rely upon the hard decisions on channel availability.

While cyclic prefix (CP) is no larger than the delay span of wireless channels in an orthogonal frequency division multiplexing (OFDM) system, inter-block interference (IBI) and inter-carrier interference (ICI) will occur and the performance of the system will be deteriorated. If OFDM is designed with long enough CP, the efficiency of OFDM modulation is significantly reduced. To effectively mitigate interference over channel with large delay spreads, pre-processing approaches at transmitters based on full channel state information (CSI) have been proposed. However, feeding full CSI back will occupy significant bandwidth and is impractical sometimes. Therefore, pre-processing optimization exploiting limited CSI feedback is investigated in this paper. An pre-processing optimization approaches for IBI and ICI mitigation has been developed and tested. Computer simulation result shows that the proposed optimization algorithm can effectively cancel IBI and ICI over channels with large delay spreads and significantly improve the performance for OFDM systems.

In this paper, we propose probability-based resource allocation in cognitive radio (CR) networks to exploit the flexibility of opportunistic spectrum access (OSA). Assisted by the statistical information acquired from spectrum sensing, the proposed approach maximizes the overall utility of CR users and ensures sufficient protection of licensed users from unacceptable interference. It also supports diverse quality-of-service (QoS) requirements of multiple CR users and allows distributed implementation. Simulation results demonstrate the effectiveness of the approach as well as its advantage over any conventional approach that ignores the statistical information.

To take advantage of time-varying spectrum opportunities, acognitiveradio(CR) network monitors the dynamic usage of the licensed band through cooperative spectrum sensing. In this paper, we propose a probability-based scheme for combination of spectrum sensing information collected from several CR users. Different from conventional cooperative spectrum sensing schemes that assume synchronous local sensing information, our scheme enables combination of both synchronous and asynchronous sensing information by utilizing the statistics of licensed band occupancy. In our scheme, the amount of information from each CR user is flexible and a simplified implementation is also feasible under a symmetrical case. Simulation results demonstrate that our scheme is robust and superior in terms of detection performance.

In conventional MIMO cellular systems, the spatial transmission mode, e.g. spatial multiplexing or transmit diversity, is chosen independently in each cell. Unfortunately, the optimum transmission mode for users that are interference limited depends to a large extent on the transmission mode used by interfering base stations. This paper proposes interference-aware link adaptation where base stations exchange their transmission plans with neighboring base stations and broadcast this information to the active users. Each user measures its long term susceptibility to spatial interference and returns this information to the base station via a spatial mode table. The base stations then schedule active users according to the decisions made in interfering base stations and the preferred transmission strategies of its own users. Simulations illustrate the ergodic sum rate the performance of switching between spatial multiplexing and statistical beamforming in different spatially correlated channels.

In this paper, we propose a relay-assisted transmission scheme in cognitive radio (CR) to exploit spatial spectrum holes, which are generated by relay techniques. The proposed scheme enables CR users to coexist with primary users at the same time in the same geographic area and spectrum band. Compared to conventional schemes, a higher spectrum efficiency is achieved by our method. We further analyze the successful communication probability and present numerical results to show advantages of our method.

Spectrum hole (SH) is defined as a spectrum band that can be utilized by unlicensed users, which is a basic resource for cognitive radio (CR) systems. Most of existing contributions detect SHs by sensing whether a primary signal is present or absent and then try to access them so that the CR and primary users use the spectrum band either at different time slots or in different geographic regions. In this paper, we propose a novel scheme with relays or directional relays for CR users to exploit new spectrum opportunity, called spatial SH. It can provide higher spectrum efficiency by coexistence of primary and CR users at the same region, time, and spectrum band. In particular, when the spectrum opportunity of a direct link from a CR transmitter to a CR receiver does not appear, our scheme may still establish the communication through indirect links, i.e., other CR users act as relay stations to assist the communication by using other spatial domains. Furthermore, we analyze the successful communication probabilities of CR users and demonstrate that the spectrum efficiency can be considerably improved by our scheme.

Probability-based strategies are proposed in this letter to determine the optimal inter-sensing duration and power control for cognitive radio (CR). With utilization of the statistics of licensed band occupancy, appropriate inter-sensing duration is determined to capture the recurrence of spectrum opportunity in time when the licensed signal is detected, or to achieve the maximum spectrum efficiency under a certain level of interference with licensed communication when the licensed signal is declared absent. Transmit power is varied dynamically according to the non-interfering probability at each sample so as to increase the transmission rate and decrease the interference power.

In this paper, we propose a cognitive radio (CR) transmission scheme, which enables secondary users to coexist with primary users by exploiting spatial spectrum holes (SSHs) through directional antennas or antenna arrays with beamforming. To ensure reliable CR links and avoid interference to primary users, some CR users may act as relays . We investigate successful communication probability of CR users when this scheme is applied. We further demonstrate that the spectrum efficiency can be greatly improved by multiplexing CR links with directional transmission.

In this paper, detection timing and channel selection for periodic spectrum sensing are investigated to improve the performance of cognitive radio (CR) users. Designed to maximize the channel efficiency of CR users under a given level of interference with licensed users, the detection timing scheme utilizes the statistics of the licensed channel occupancy to determine the optimal starting point of each sensing action. A channel selection scheme in the multichannel multiuser environment is also proposed to specify which channel to detect for the upcoming sensing action based on detection timing. Numerical results demonstrate that our schemes considerably improve the overall channel efficiency while protecting the communication among licensed users.

In this paper, we work on maximizing the capacity of the reverse link of a CDMA wireless network. Oh and Soong (2006) presented an information-theoretic capacity model for analyzing this system. That formulation produces solutions that often result in unfairness allocation of power to most users. Here, we propose the addition of a maximum capacity constraint into the problem, thereby creating a more fair power allocation scheme. First, we improve on the algorithm presented in (Oh and Soong, 2006) by proposing a closed form solution and an algorithm which works nine times faster. Then, we propose a closed form algorithm for solving the new enhanced problem.

We discuss the information-theoretic approach to finding the pattern of transmission powers of the stations in a CDMA system which maximizes the aggregate capacity of the reverse link. This optimization problem is solved subject to a set of constraints. Previous research has suggested a minimum guaranteed quality of service plus bounds on individual transmission powers and the aggregate transmitted power as the constraints. Solving this problem, it is found out that the solution is very prone to including one station which transmits at a rate a hundred times as much as the others. Thus, it is concluded that the above constraints are not enough to produce a solution which can be realized in an actual system. It is suggested that lack of any constraint which explicitly controls either the maximum capacity of each station or the unfairness of the whole system is responsible for this shortcoming. We include a maximum capacity constraint into the formulation and propose an algorithm for solving the resulting optimization problem. Then, empirical evidence are analyzed to show that the system actually becomes more balanced and practical after the new constraint is added to it.

By controlling the pattern of transmission powers of the stations in a CDMA system, the aggregate capacity of the reverse link can be optimized. To make this problem practically applicable, appropriate constraints should be added to it. In previous research, bounds on transmission power, lower limit on signal to noise ratio, and maximum capacity of single stations plus a maximum bound on the aggregate transmission power of the system were considered. However, none of these constraints directly controls the capacity share of the single stations. Hence, the solution might exhibit a transmission power pattern in which, for example, one third of the whole capacity is given to a single station. This increases the probability of the base station depending massively on one station, resulting in a major loss when that station stops transmitting. In this paper, we introduce another constraint into the available set. This way, we reformulate the available problem by adding a maximum capacity share constraint to it and propose an algorithm for solving it. The paper includes mathematical analysis of the problem and experimental results.

The communication system is currently undergoing a convergence to IP services. As a result, voice over internet protocol (VoIP) will be commonplace in the near future. In order to maximize the voice capacity, the overhead associated with controlling VoIP transmissions must be carefully managed. The current efforts in B3G (beyond 3G) standards development to efficiently control VoIP transmissions by grouping VoIP users into scheduling groups, assigning the group a set of shared time-frequency resources, and using bitmap signaling to allocate resources were detailed in [1]. This paper introduces several improvement mechanisms which enhance the basic concept outlined in [1]. System level simulations are used to validate the improved signaling technique and show that the technique can efficiently support 133 VoIP users per megahertz in a VoIP only system and 64 VoIP users per megahertz plus 1.05 Mbps for the traffic mixed considered in a mixed VoIP/data system.

With channel state information (CSI) at the transmitter, beamforming can be used for spatial diversity and multiple spatial access. Due to latency and feedback bandwidth limitation, the CSI at the transmitter is often known with some ambiguity. In this paper, we develop a robust method for downlink beamforming that takes the ambiguity of the CSI into consideration. It is shown by computer simulation that, compared with the existing method, the required signal-to-noise ratio (SNR) for a 1% bit-error rate (BER) is reduced by over 2 dB for a system with 4 transmit antennas and 2 users when the variance of the CSI is -20 dB. The performance gain increases with the number of transmit antennas when the number of users is fixed. The required SNR for a 1% BER is reduced by over 4 dB if the the number of transmitter antennas is 8. We also study the impact of power allocation on the downlink beamforming.

Transmit and receive antenna arrays can be used to form multiple-input and multiple-output (MIMO) systems for improving the reliability and capacity of data transmission. Layered space-time coding with decision-feedback detection is a promising technique for future wireless communications. In this paper, we investigate power allocation at the transmitter to improve the performance of the decision-feedback detection. The proposed power allocation method may only depend on or is even independent of the signal-to-noise ratio (SNR) of the MIMO systems. When the SNR at the transmitter is not available, the power of each data stream is allocated according to the required bit-error-rate (BER) of the system. Computer simulation shows that the proposed method can improve the performance of a 2-input and 2-output system by 4 dB at 1% BER and that of a 4-input and 4-output system by 3.5 dB.

In this paper, we investigate several efficient interpolation techniques for pilot symbol assisted channel estimation in OFDM. The interpolation methods studied include two dimensional (2-D) separable lowpass sine interpolator with Kaiser window, 2-D separable Deslauriers-Dubuc (DD) interpolation and 2-D discrete Fourier transform (DFT) based lowpass interpolation. The performances of these interpolators are compared with those of the well known minimum mean-square error (MMSE) 2-D separable Wiener filter and the perfect channel state information. It is shown that the Kaiser window based interpolator and DD interpolation are simple, robust, and outperform the 2-D DFT based lowpass interpolation as well as several existing interpolation methods proposed in the literature. These two schemes are suitable candidates for use in 1-D and 2-D channel estimation

The information-theoretic sum capacity of reverse link CDMA systems with QoS constraints is investigated in this paper. Since the reverse link of CDMA systems are, for a given channel and noise conditions, interference-limited, the sum capacity can be achieved by optimally allocating the transmit powers of the mobile stations with the optimal (Shannon) coding. Unfortunately, the sum capacity is usually achieved via unfair resource allocation. This can be avoided by imposing QoS constraints on the system. The results here show that for a single cell system, the sum capacity can be achieved while meeting the QoS constraints with a semi-bang-bang power allocation strategy. Numerical results are then presented to show the multi-user diversity gain and the impact of QoS constraints. The implication of TDM operation in a practical reverse link CDMA system is also discussed.

This paper investigates the design of practical sine interpolation filters in pilot symbol assisted modulation (PSAM) systems. By closely examining the error mechanism in PSAM channel estimation, we show that the error floor phenomenon is caused by the non-ideal characteristic of the interpolation filter. Based on the use of adjustable window functions, we present a set of design guidelines to determine the shape of window functions, the window/filter length and the pilot insertion rate. The design choices essentially reflect the trade-offs between error performance, implementation complexity and transmission rate.

There has been keen interest in the literature recently on the IEEE wireless metropolitan area network (MAN) developed within IEEE 802.16. Through the use of flexible physical layer features and medium access control (MAC) layer mechanisms, this system can be used to deliver broadband voice and data into areas that may have a wide range of population densities, cell radii, propagation environments, and quality of service (QoS) requirements. The physical layer provides flexibilities of time or frequency domain duplexing, multiple bandwidths, adjustable subchannelization, scalable OFDM formats, adaptive coded modulation, and advanced antenna system. The IEEE 802.16 MAC layer offers a connection-oriented service to upper layers of the protocol stack. The QoS of each connection takes one of four levels: constant bit rate grant, real time polling, non-real-time polling, and best effort. The MAC layer also offers packing, fragmentation and ARQ. The MAC privacy sublayer performs authentication, key exchange and encryption of MAC packet data units. The MAC convergence sublayers at the top of the MAC enable Ethernet, ATM, TDM voice and IP (Internet Protocol) services to be offered. This presentation will endeavor to provide a high level overview of the system. It will discuss, from an information theoretic point of view, the key enablers of the system.

This paper investigates the design of practical sinc interpolation filters in pilot symbol assisted modulation (PSAM) systems. By closely examining the error mechanism in PSAM channel estimations, it is shown that the error floor phenomenon is caused by the non-ideal characteristic of the interpolation filter. We present a set of design guidelines to determine the shape of window functions, the window/filter length and the pilot insertion rate. The design choices essentially reflect the trade-offs between error performance, implementation complexity and transmission rate.

A novel forward link supervision algorithm applicable to power controlled CDMA systems is presented. This new algorithm relies upon the quality of the dedicated power control commands and is therefore compatible with systems that offer packet data service without an assigned dedicated Walsh code channel such as that found in commercial systems denned by IS-2000 Rev C. The algorithm is analyzed both analytically and with simulations. The conclusion from these analyzes show that the proposed forward link supervision algorithm does not affect the call quality, minimizes the impact on the reverse link capacity from unreliable power control commands and leads to call termination only if necessary.

The information-theoretic sum capacity of reverse link CDMA systems is investigated in this paper. As the reverse link CDMA systems are interference-limited, for given channel and noise conditions, the information-theoretic system capacity can be achieved by optimally allocating the transmit powers of the mobile stations. The maximum capacity is often achieved by unfair resource allocation. To avoid such a case, QoS constraints are imposed to individual mobile stations. The exhaustive search of the optimal power allocation solution that maximizes the aggregate capacity, requires O(N/sup M/) computations, where M is the number of the mobile station in the system and N is the granularity of the transmit power of a mobile station. The paper shows that for a single cell, the optimal power allocation solution can be found by polynomial times of computations, without sacrificing the optimality. Numerical results are presented to show the multi-user diversity gain and the impact of QoS constraints.

A novel multistage successive interference cancellation scheme is proposed which operates on the reverse code-division multiple-access (CDMA) link using binary phase shift keying (BPSK) modulation, coherent detection and reference symbols to obtain channel estimates. The results of a single cell multiuser investigation demonstrate increased traffic capacity. However, this increase is initially very moderate due to corruption of the channel estimates by interference from symbols not yet demodulated and cancelled. A modification in the transmitted signal structure addressing this problem is proposed. The results of a single cell analysis of the modified cancellation scheme demonstrate that the system's traffic capacity reaches approximately 80% of that of a multistage successive interference cancelling receiver operating with the perfect knowledge of channel parameters. A subsequent multicell investigation shows that for a hexagonal cell geometry with a path loss exponent of four and without any forward error correction (FEC) coding or cell sectorization, the system capacity compares very favorably with that of the IS-95 system, which employs powerful error control coding. Capacities with other path loss exponents and cell geometries are also investigated. The results show a substantial traffic capacity increase over that of a comparable receiver without interference cancellation.